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Obesity Research

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Over the years, NHLBI-supported research on overweight and obesity has led to the development of evidence-based prevention and treatment guidelines for healthcare providers. NHLBI research has also led to guidance on how to choose a behavioral weight loss program.

Studies show that the skills learned and support offered by these programs can help most people make the necessary lifestyle changes for weight loss and reduce their risk of serious health conditions such as heart disease and diabetes.

Our research has also evaluated new community-based programs for various demographics, addressing the health disparities in overweight and obesity.

NHLBI research that really made a difference

• In 1991, the NHLBI developed an Obesity Education Initiative to educate the public and health professionals about obesity as an independent risk factor for cardiovascular disease and its relationship to other risk factors, such as high blood pressure and high blood cholesterol. The initiative led to the development of clinical guidelines for treating overweight and obesity.
• The NHLBI and other NIH Institutes funded the Obesity-Related Behavioral Intervention Trials (ORBIT) projects , which led to the ORBIT model for developing behavioral treatments to prevent or manage chronic diseases. These studies included families and a variety of demographic groups. A key finding from one study focuses on the importance of targeting psychological factors in obesity treatment.

Current research funded by the NHLBI

The Division of Cardiovascular Sciences , which includes the Clinical Applications and Prevention Branch, funds research to understand how obesity relates to heart disease. The Center for Translation Research and Implementation Science supports the translation and implementation of research, including obesity research, into clinical practice. The Division of Lung Diseases and its National Center on Sleep Disorders Research fund research on the impact of obesity on sleep-disordered breathing.

Find funding opportunities and program contacts for research related to obesity and its complications.

Current research on obesity and health disparities

Health disparities happen when members of a group experience negative impacts on their health because of where they live, their racial or ethnic background, how much money they make, or how much education they received. NHLBI-supported research aims to discover the factors that contribute to health disparities and test ways to eliminate them.

• NHLBI-funded researchers behind the RURAL: Risk Underlying Rural Areas Longitudinal Cohort Study want to discover why people in poor rural communities in the South have shorter, unhealthier lives on average. The study includes 4,000 diverse participants (ages 35–64 years, 50% women, 44% whites, 45% Blacks, 10% Hispanic) from 10 of the poorest rural counties in Kentucky, Alabama, Mississippi, and Louisiana. Their results will support future interventions and disease prevention efforts.
• The Hispanic Community Health Study/Study of Latinos (HCHS/SOL) is looking at what factors contribute to the higher-than-expected numbers of Hispanics/Latinos who suffer from metabolic diseases such as obesity and diabetes. The study includes more than 16,000 Hispanic/Latino adults across the nation.

Find more NHLBI-funded studies on obesity and health disparities at NIH RePORTER.

Read how African Americans are learning to transform soul food into healthy, delicious meals to prevent cardiovascular disease: Vegan soul food: Will it help fight heart disease, obesity?

Current research on obesity in pregnancy and childhood

• The NHLBI-supported Fragile Families Cardiovascular Health Follow-Up Study continues a study that began in 2000 with 5,000 American children born in large cities. The cohort was racially and ethnically diverse, with approximately 40% of the children living in poverty. Researchers collected socioeconomic, demographic, neighborhood, genetic, and developmental data from the participants. In this next phase, researchers will continue to collect similar data from the participants, who are now young adults.
• The NHLBI is supporting national adoption of the Bright Bodies program through Dissemination and Implementation of the Bright Bodies Intervention for Childhood Obesity . Bright Bodies is a high-intensity, family-based intervention for childhood obesity. In 2017, a U.S. Preventive Services Task Force found that Bright Bodies lowered children’s body mass index (BMI) more than other interventions did.
• The NHLBI supports the continuation of the nuMoM2b Heart Health Study , which has followed a diverse cohort of 4,475 women during their first pregnancy. The women provided data and specimens for up to 7 years after the birth of their children. Researchers are now conducting a follow-up study on the relationship between problems during pregnancy and future cardiovascular disease. Women who are pregnant and have obesity are at greater risk than other pregnant women for health problems that can affect mother and baby during pregnancy, at birth, and later in life.

Find more NHLBI-funded studies on obesity in pregnancy and childhood at NIH RePORTER.

Learn about the largest public health nonprofit for Black and African American women and girls in the United States: Empowering Women to Get Healthy, One Step at a Time .

Current research on obesity and sleep

• An NHLBI-funded study is looking at whether energy balance and obesity affect sleep in the same way that a lack of good-quality sleep affects obesity. The researchers are recruiting equal numbers of men and women to include sex differences in their study of how obesity affects sleep quality and circadian rhythms.
• NHLBI-funded researchers are studying metabolism and obstructive sleep apnea . Many people with obesity have sleep apnea. The researchers will look at the measurable metabolic changes in participants from a previous study. These participants were randomized to one of three treatments for sleep apnea: weight loss alone, positive airway pressure (PAP) alone, or combined weight loss and PAP. Researchers hope that the results of the study will allow a more personalized approach to diagnosing and treating sleep apnea.
• The NHLBI-funded Lipidomics Biomarkers Link Sleep Restriction to Adiposity Phenotype, Diabetes, and Cardiovascular Risk study explores the relationship between disrupted sleep patterns and diabetes. It uses data from the long-running Multiethnic Cohort Study, which has recruited more than 210,000 participants from five ethnic groups. Researchers are searching for a cellular-level change that can be measured and can predict the onset of diabetes in people who are chronically sleep deprived. Obesity is a common symptom that people with sleep issues have during the onset of diabetes.

Find more NHLBI-funded studies on obesity and sleep at NIH RePORTER.

Learn about a recent study that supports the need for healthy sleep habits from birth: Study finds link between sleep habits and weight gain in newborns .

Obesity research labs at the NHLBI

The Cardiovascular Branch and its Laboratory of Inflammation and Cardiometabolic Diseases conducts studies to understand the links between inflammation, atherosclerosis, and metabolic diseases.

NHLBI’s Division of Intramural Research , including its Laboratory of Obesity and Aging Research , seeks to understand how obesity induces metabolic disorders. The lab studies the “obesity-aging” paradox: how the average American gains more weight as they get older, even when food intake decreases.

Related obesity programs and guidelines

• Aim for a Healthy Weight is a self-guided weight-loss program led by the NHLBI that is based on the psychology of change. It includes tested strategies for eating right and moving more.
• The NHLBI developed the We Can! ® (Ways to Enhance Children’s Activity & Nutrition) program to help support parents in developing healthy habits for their children.
• The Accumulating Data to Optimally Predict obesity Treatment (ADOPT) Core Measures Project standardizes data collected from the various studies of obesity treatments so the data can be analyzed together. The bigger the dataset, the more confidence can be placed in the conclusions. The main goal of this project is to understand the individual differences between people who experience the same treatment.
• The NHLBI Director co-chairs the NIH Nutrition Research Task Force, which guided the development of the first NIH-wide strategic plan for nutrition research being conducted over the next 10 years. See the 2020–2030 Strategic Plan for NIH Nutrition Research .
• The NHLBI is an active member of the National Collaborative on Childhood Obesity (NCCOR) , which is a public–private partnership to accelerate progress in reducing childhood obesity.
• The NHLBI has been providing guidance to physicians on the diagnosis, prevention, and treatment of obesity since 1977. In 2017, the NHLBI convened a panel of experts to take on some of the pressing questions facing the obesity research community. See their responses: Expert Panel on Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents (PDF, 3.69 MB).
• In 2021, the NHLBI held a Long Non-coding (lnc) RNAs Symposium to discuss research opportunities on lnc RNAs, which appear to play a role in the development of metabolic diseases such as obesity.
• The Muscatine Heart Study began enrolling children in 1970. By 1981, more than 11,000 students from Muscatine, Iowa, had taken surveys twice a year. The study is the longest-running study of cardiovascular risk factors in children in the United States. Today, many of the earliest participants and their children are still involved in the study, which has already shown that early habits affect cardiovascular health later in life.
• The Jackson Heart Study is a unique partnership of the NHLBI, three colleges and universities, and the Jackson, Miss., community. Its mission is to discover what factors contribute to the high prevalence of cardiovascular disease among African Americans. Researchers aim to test new approaches for reducing this health disparity. The study incudes more than 5,000 individuals. Among the study’s findings to date is a gene variant in African Americans that doubles the risk of heart disease.

Explore more NHLBI research on overweight and obesity

The sections above provide you with the highlights of NHLBI-supported research on overweight and obesity . You can explore the full list of NHLBI-funded studies on the NIH RePORTER .

To find more studies:

• Type your search words into the  Quick Search  box and press enter. 
• Check  Active Projects  if you want current research.
• Select the  Agencies  arrow, then the  NIH  arrow, then check  NHLBI .

If you want to sort the projects by budget size — from the biggest to the smallest — click on the  FY Total Cost by IC  column heading.

470 Obesity Essay Topic Ideas & Examples

Looking for obesity essay topics? Being a serious problem, obesity is definitely worth writing about.

NIH-Supported Obesity Research

The NIH Obesity Research Task Force promotes collaboration and coordination across the NIH to accelerate progress in obesity research.

Funding Opportunities for Research

View current and past NIH notices of funding opportunities for obesity research.

Meetings & Workshops for Obesity Researchers

NIH convenes scientific meetings and workshops on obesity research throughout the year.

Strategic Plan for NIH Obesity Research

The Strategic Plan for NIH Obesity Research serves as a guide to accelerate a broad spectrum of research toward developing new and more effective approaches to address the tremendous burden of obesity, so that people can look forward to healthier lives.

The Plan was originally published in 2011. In 2018-2019, the Obesity Research Task Force confirmed that the challenges and opportunities identified in the Plan reflect the current research landscape and should continue to guide obesity research.

• Full Report for the scientific community (PDF, 716.76 KB)
• Summary Report non-technical (PDF, 627.47 KB)

Looking for Clinical Trials Related to Obesity?

Clinical trials offer hope for many people and an opportunity to help researchers find better treatments for others in the future.

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Perspective

The Perspective section provides experts with a forum to comment on topical or controversial issues of broad interest.

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Obesity research: Moving from bench to bedside to population

* E-mail: [email protected]

Affiliation Diabetes Research Program, Department of Medicine, New York University Grossman School of Medicine, New York, New York, United States of America

• Ann Marie Schmidt

Published: December 4, 2023

• https://doi.org/10.1371/journal.pbio.3002448
• Reader Comments

Globally, obesity is on the rise. Research over the past 20 years has highlighted the far-reaching multisystem complications of obesity, but a better understanding of its complex pathogenesis is needed to identify safe and lasting solutions.

Citation: Schmidt AM (2023) Obesity research: Moving from bench to bedside to population. PLoS Biol 21(12): e3002448. https://doi.org/10.1371/journal.pbio.3002448

Copyright: © 2023 Ann Marie Schmidt. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: AMS received funding from U.S. Public Health Service (grants 2P01HL131481 and P01HL146367). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The author has declared that no competing interests exist.

Abbreviations: EDC, endocrine disruptor chemical; GIP, gastric inhibitory polypeptide; GLP1, glucagon-like peptide 1; HFCS, high-fructose corn syrup

This article is part of the PLOS Biology 20th anniversary collection.

Obesity is a multifaceted disorder, affecting individuals across their life span, with increased prevalence in persons from underrepresented groups. The complexity of obesity is underscored by the multiple hypotheses proposed to pinpoint its seminal mechanisms, such as the “energy balance” hypothesis and the “carbohydrate–insulin” model. It is generally accepted that host (including genetic factors)–environment interactions have critical roles in this disease. The recently framed “fructose survival hypothesis” proposes that high-fructose corn syrup (HFCS), through reduction in the cellular content of ATP, stimulates glycolysis and reduces mitochondrial oxidative phosphorylation, processes that stimulate hunger, foraging, weight gain, and fat accumulation [ 1 ]. The marked upswing in the use of HFCS in beverages and foods, beginning in the 1980s, has coincided with the rising prevalence of obesity.

The past few decades of scientific progress have dramatically transformed our understanding of pathogenic mechanisms of obesity ( Fig 1 ). Fundamental roles for inflammation were unveiled by the discovery that tumor necrosis factor-α contributed to insulin resistance and the risk for type 2 diabetes in obesity [ 2 ]. Recent work has ascribed contributory roles for multiple immune cell types, such as monocytes/macrophages, neutrophils, T cells, B cells, dendritic cells, and mast cells, in disturbances in glucose and insulin homeostasis in obesity. In the central nervous system, microglia and their interactions with hypothalamic neurons affect food intake, energy expenditure, and insulin sensitivity. In addition to cell-specific contributions of central and peripheral immune cells in obesity, roles for interorgan communication have been described. Extracellular vesicles emitted from immune cells and from adipocytes, as examples, are potent transmitters of obesogenic species that transfer diverse cargo, including microRNAs, proteins, metabolites, lipids, and organelles (such as mitochondria) to distant organs, affecting functions such as insulin sensitivity and, strikingly, cognition, through connections to the brain [ 3 ].

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Basic, clinical/translational, and epidemiological research has made great strides in the past few decades in uncovering novel components of cell-intrinsic, intercellular, and interorgan communications that contribute to the pathogenesis of obesity. Both endogenous and exogenous (environmental) stressors contribute to the myriad of metabolic perturbations that impact energy intake and expenditure; mediate innate disturbances in the multiple cell types affected in obesity in metabolic organelles and organs, including in immune cells; and impair beneficial interkingdom interactions of the mammalian host with the gut microbiome. The past few decades have also witnessed remarkable efforts to successfully treat obesity, such as the use of the incretin agonists and bariatric surgery. Yet, these and other strategies may be accompanied by resistance to weight loss, weight regain, adverse effects of interventions, and the challenges of lifelong implementation. Hence, through leveraging novel discoveries from the bench to the bedside to the population, additional strategies to prevent obesity and weight regain post-weight loss, such as the use of “wearables,” with potential for implementation of immediate and personalized behavior modifications, may hold great promise as complementary strategies to prevent and identify lasting treatments for obesity. Figure created with BioRender.

https://doi.org/10.1371/journal.pbio.3002448.g001

Beyond intercellular communication mediated by extracellular vesicles, the discovery of interactions between the host and the gut microbiome has suggested important roles for this interkingdom axis in obesity. Although disturbances in commensal gut microbiota species and their causal links to obesity are still debated, transplantation studies have demonstrated relationships between Firmicutes/Bacteroidetes ratios and obesity [ 4 ]. Evidence supports the concept that modulation of gut microbiota phyla modulates fundamental activities, such as thermogenesis and bile acid and lipid metabolism. Furthermore, compelling discoveries during the past few decades have illustrated specific mechanisms within adipocytes that exert profound effects on organismal homeostasis, such as adipose creatine metabolism, transforming growth factor/SMAD signaling, fibrosis [ 5 ], hypoxia and angiogenesis, mitochondrial dysfunction, cellular senescence, impairments in autophagy, and modulation of the circadian rhythm. Collectively, these recent discoveries set the stage for the identification of potential new therapeutic approaches in obesity.

Although the above discoveries focus largely on perturbations in energy metabolism (energy intake and expenditure) as drivers of obesity, a recently published study suggests that revisiting the timeline of obesogenic forces in 20th and 21st century society may be required. The authors tracked 320,962 Danish schoolchildren (born during 1930 to 1976) and 205,153 Danish male military conscripts (born during 1939 to 1959). Although the overall trend of the percentiles of the distributions of body mass index were linear across the years of birth, with percentiles below the 75th being nearly stable, those above the 75th percentile demonstrated a steadily steeper rise the more extreme the percentile; this was noted in the schoolchildren and the military conscripts [ 6 ]. The authors concluded that the emergence of the obesity epidemic might have preceded the appearance of the factors typically ascribed to mediating the obesogenic transformation of society by several decades. What are these underlying factors and their yet-to-be-discovered mechanisms?

First, in terms of endogenous factors relevant to individuals, stressors such as insufficient sleep and psychosocial stress may impact substrate metabolism, circulating appetite hormones, hunger, satiety, and weight gain [ 7 ]. Reduced access to healthy foods rich in vegetables and fruits but easy access to ultraprocessed ingredients in “food deserts” and “food swamps” caused excessive caloric intake and weight gain in clinical studies [ 8 ]. Second, exogenous environmental stresses have been associated with obesity. For example, air pollution has been directly linked to adipose tissue dysfunction [ 9 ], and ubiquitous endocrine disruptor chemicals (EDCs) such as bisphenols and phthalates (found in many items of daily life including plastics, food, clothing, cosmetics, and paper) are linked to metabolic dysfunction and the development of obesity [ 10 ]. Hence, factors specific to individuals and their environment may exacerbate their predisposition to obesity.

In addition to the effects of exposure to endogenous and exogenous stressors on the risk of obesity, transgenerational (passed through generations without direct exposure of stimulant) and intergenerational (direct exposure across generations) transmission of these stressors has also been demonstrated. A leading proposed mechanism is through epigenetic modulation of the genome, which then predisposes affected offspring to exacerbated responses to obesogenic conditions such as diet. A recent study suggested that transmission of disease risk might be mediated through transfer of maternal oocyte-derived dysfunctional mitochondria from mothers with obesity [ 11 ]. Additional mechanisms imparting obesogenic “memory” may be evoked through “trained immunity.”

Strikingly, the work of the past few decades has resulted in profound triumphs in the treatment of obesity. Multiple approved glucagon-like peptide 1 (GLP1) and gastric inhibitory polypeptide (GIP) agonists [ 12 ] (alone or in combinations) induce highly significant weight loss in persons with obesity [ 13 ]. However, adverse effects of these agents, such as pancreatitis and biliary disorders, have been reported [ 14 ]. Therefore, the long-term safety and tolerability of these drugs is yet to be determined. In addition to pharmacological agents, bariatric surgery has led to significant weight loss as well. However, efforts to induce weight loss through reduction in caloric intake and increased physical activity, pharmacological approaches, and bariatric surgery may not mediate long-term cures in obesity on account of resistance to weight loss, weight regain, adverse effects of interventions, and the challenges of lifelong implementation of these measures.

Where might efforts in combating obesity lie in the next decades? At the level of basic and translational science, the heterogeneity of metabolic organs could be uncovered through state-of-the-art spatial “omics” and single-cell RNA sequencing approaches. For example, analogous to the deepening understanding of the great diversity in immune cell subsets in homeostasis and disease, adipocyte heterogeneity has also been suggested, which may reflect nuances in pathogenesis and treatment approaches. Further, approaches to bolster brown fat and thermogenesis may offer promise to combat evolutionary forces to hoard and store fat. A better understanding of which interorgan communications may drive obesity will require intensive profiling of extracellular vesicles shed from multiple metabolic organs to identify their cargo and, critically, their destinations. In the three-dimensional space, the generation of organs-on-a-chip may facilitate the discovery of intermetabolic organ communications and their perturbations in the pathogenesis of obesity and the screening of new therapies.

Looking to prevention, recent epidemiological studies suggest that efforts to tackle obesity require intervention at multiple levels. The institution of public health policies to reduce air pollution and the vast employment of EDCs in common household products could impact the obesity epidemic. Where possible, the availability of fresh, healthy foods in lieu of highly processed foods may be of benefit. At the individual level, focused attention on day-to-day behaviors may yield long-term benefit in stemming the tide of obesity. “Wearable” devices that continuously monitor the quantity, timing, and patterns of food intake, physical activity, sleep duration and quality, and glycemic variability might stimulate on-the-spot and personalized behavior modulation to contribute to the prevention of obesity or of maintenance of the weight-reduced state.

Given the involvement of experts with wide-ranging expertise in the science of obesity, from basic science, through clinical/translational research to epidemiology and public health, it is reasonable to anticipate that the work of the next 2 decades will integrate burgeoning multidisciplinary discoveries to drive improved efforts to treat and prevent obesity.

Acknowledgments

The author is grateful to Ms. Latoya Woods of the Diabetes Research Program for assistance with the preparation of the manuscript and to Ms. Kristen Dancel-Manning for preparation of the Figure accompanying the manuscript.

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A systematic literature review on obesity: Understanding the causes & consequences of obesity and reviewing various machine learning approaches used to predict obesity

Affiliations.

• 1 Centre for Software Technology and Management, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), Bangi, 43600, Selangor, Malaysia.
• 2 Centre for Software Technology and Management, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), Bangi, 43600, Selangor, Malaysia. Electronic address: [email protected].
• 3 RIADI Laboratory, University of Manouba, Manouba, Tunisia; College of Computer Science and Engineering, Taibah University, Medina, Saudi Arabia.
• 4 Center for Artificial Intelligence Technology, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), Bangi, 43600, Selangor, Malaysia.
• PMID: 34426171
• DOI: 10.1016/j.compbiomed.2021.104754

Obesity is considered a principal public health concern and ranked as the fifth foremost reason for death globally. Overweight and obesity are one of the main lifestyle illnesses that leads to further health concerns and contributes to numerous chronic diseases, including cancers, diabetes, metabolic syndrome, and cardiovascular diseases. The World Health Organization also predicted that 30% of death in the world will be initiated with lifestyle diseases in 2030 and can be stopped through the suitable identification and addressing of associated risk factors and behavioral involvement policies. Thus, detecting and diagnosing obesity as early as possible is crucial. Therefore, the machine learning approach is a promising solution to early predictions of obesity and the risk of overweight because it can offer quick, immediate, and accurate identification of risk factors and condition likelihoods. The present study conducted a systematic literature review to examine obesity research and machine learning techniques for the prevention and treatment of obesity from 2010 to 2020. Accordingly, 93 papers are identified from the review articles as primary studies from an initial pool of over 700 papers addressing obesity. Consequently, this study initially recognized the significant potential factors that influence and cause adult obesity. Next, the main diseases and health consequences of obesity and overweight are investigated. Ultimately, this study recognized the machine learning methods that can be used for the prediction of obesity. Finally, this study seeks to support decision-makers looking to understand the impact of obesity on health in the general population and identify outcomes that can be used to guide health authorities and public health to further mitigate threats and effectively guide obese people globally.

Keywords: Diseases; Machine learning; Obesity; Overweight; Risk factors.

Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Publication types

• Research Support, Non-U.S. Gov't
• Systematic Review
• Machine Learning
• Metabolic Syndrome*
• Obesity* / epidemiology
• Risk Factors

Nutrition Obesity Research Program

The Nutrition Obesity Research Program brings together clinical expertise and collaborative research to understand causes of obesity and find new treatment options.

The Nutrition Obesity Research Program is the first step toward a comprehensive depository of obesity solutions, evolving treatment and clinical management through increased understanding of obesity physiology.

Our program at Mayo Clinic is poised to make a transformational change to address the complex health challenges of obesity. Our team is developing patient-centered approaches to obesity management that leverage the Mayo Clinic Model of Care, clinical expertise and collaborative research. Through our coordinated research efforts and studies, we're beginning to understand the drivers of weight gain and obesity and the associated health complications at the molecular, cellular and individual levels.

The Nutrition Obesity Research Program is jointly based at Mayo Clinic's campuses in Phoenix/Scottsdale, Arizona; Jacksonville, Florida; and Rochester, Minnesota. In addition to our ongoing research, clinicians at each site provide care and services for people with needs and concerns related to nutrition and obesity.

Our scientists have a broad and deep understanding of the cellular and molecular basis of how and where fat is stored. This knowledge helps us understand the likelihood of disease and contributing factors to cancer risk and lifelong health conditions. It also helps us understand underlying health problems that affect long-term health span and quality of life.

The broad spectrum of research initiatives in the Nutrition Obesity Research Program provides a foundation for the ability to deliver transformative insight into new and diverse areas of research. Ultimately, our researchers and clinicians hope to prevent and possibly cure obesity through interdisciplinary collaboration.

Care and support

For people affected by obesity or related diagnoses, clinicians and scientists in the Nutrition Obesity Research Program at Mayo Clinic offer:

• Opportunities to participate in clinical research projects, special programs and clinical trials.
• Information, education and activities for research participants and caregivers.

Program directors

Three directors guide research and clinical efforts within the Nutrition Obesity Research Program.

• Andres J. Acosta, M.D., Ph.D. Dr. Acosta is a bariatrician and gastroenterologist at Mayo Clinic in Rochester, Minnesota. Dr. Acosta conducts research on gastrointestinal physiology to understand the complexity of food intake regulation and obesity. Read more about Dr. Acosta .
• Maria L. Collazo-Clavell, M.D. Dr. Collazo-Clavell is an endocrinologist at Mayo Clinic in Rochester, Minnesota, who has been using innovative care models for people with obesity for more than 25 years. Her research interests include the clinical study of obesity and its complications, especially type 2 diabetes. Read more about Dr. Collazo-Clavell .
• Mark A. McNiven, Ph.D. Dr. McNiven brings his expertise in biochemistry and molecular biology to the study of gastroenterology, including the liver and pancreas. Dr. McNiven's extensive research includes the study of cell function and fat storage and metabolism. Read more about Dr. McNiven .

Contact us about our research on obesity, data sharing, education or support opportunities.

Patient Appointments

Both patients and medical professionals can request appointments and referrals to Mayo Clinic for concerns related to nutrition, obesity and overweight.

About Obesity

• Obesity - About Obesity Obesity
• Diabetes - About Obesity Diabetes
• Metabolic syndrome - About Obesity Metabolic syndrome
• Nonalcoholic fatty liver disease - About Obesity Nonalcoholic fatty liver disease

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394 Obesity Essay Topics & Research Questions + Examples

Are you looking for the best obesity essay topics? You are at the right place! We’ve compiled a list of obesity research questions and catchy titles about various aspects of this problem. Read on to discover the most controversial topics about obesity for your research paper, project, argumentative essay, persuasive speech, and other assignments.

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• The Causes and Effects of Obesity
• Childhood Obesity: Causes and Effects
• Childhood Obesity: The Parents’ Responsibility
• Childhood Obesity: Causes and Solutions
• Health Promotion Proposal Obesity Prevention
• Unhealthy Food Culture and Obesity
• Parents Are Not to Blame for Obesity in Children
• Depression as It Relates to Obesity
• Junk Food and Children’s Obesity
• Obesity Prevention and Weight Management Theory
• Health Promotion for Obesity in Adults This is a health promotion proposal for preventing obesity among adults in the US. People get obesity when they acquire a given body mass index.
• Obesity as a Disease: Arguments For and Against Although some people consider that obesity is a disease caused by biological and psychological factors, others are confident that it should not be perceived as a disease.
• Childhood Obesity Study and Health Belief Model A field experiment will be used in the research to identify the impact of a healthy lifestyle intervention on children diagnosed with obesity.
• Childhood Obesity and Health Promotion Today, childhood obesity is one of the critical health concerns. Being an important factor impacting the future of the nation, children`s health should be cultivated.
• Obesity From Sociological Perspectives The social problem under focus is obesity originating from Latino food norms. The problem of obesity is the direct result of adherence to social norms.
• Obesity: Background and Preventative Measures Obesity is an epidemic. It tends to have more negative than positive effects on the economy and can greatly reduce one’s life expectancy.
• Link Between Obesity and Genetics Obesity affects the lives through limitations implemented on the physical activity, associated disorders, and even emotional pressure.
• Obesity Management and Intervention Many patients within the age brackets of 5-9 admitted in hospital with obesity cases have a secondary diagnosis of cardiovascular disease exceptionally high blood pressure.
• How to Reduce Obesity and Maintain Health? Health is becoming a matter of grave concern, especially the health of teenagers and adolescents, who are becoming increasingly overweight and obese.
• Health Promotion Strategies for Obesity The paper outlines and critically analyses the population based strategy as a method of managing and preventing obesity used in United Kingdom.
• Obesity Issue: Application of Nursing Theory This analysis will show that well-established theories are valuable to nursing problem-solving as frameworks for analyzing issues and planning solutions.
• Obesity: A Personal Problem and a Social Issue Obesity is a problem affecting many persons and society as a whole. According to World Health Organization, over 40% of the US population is either overweight or outright obese.
• Childhood Obesity: Quantitative Annotated Bibliography Childhood obesity is a problem that stands especially acute today, in the era of consumerism. Children now have immense access to the Internet.
• Childhood Obesity and Nutrition The prevalence of childhood obesity in schools can be compared to an epidemic of a virulent disease on a global scale.
• Children Obesity Prevention Proposals The purpose of this paper is to propose the study of motivational interviewing benefits in preventing childhood obesity in the context of the literature review method.
• Childhood Obesity: Prevention and Mitigation Over the past three decades, childhood obesity has developed into an epidemic and is considered as one of the major health issues in the world.
• Children Obesity Research Method and Sampling This paper presents a research method and sampling on the investigation of the issue of childhood obesity and the impact parents` education might have on reducing excess weight.
• Obesity in Children and Adolescents: Quantitative Methods Obesity in children and adolescents has increasingly become prevalent in the recent past and is now a major problem in most developed countries.
• Obesity Prevention: Social Media Campaign A variety of programs aimed at reducing the risk of obesity has been suggested by healthcare practitioners and scholars. Among them, diet interventions are highly popular.
• Pediatric Obesity and Self-Care Nursing Theory The presence of excess body fat in children has to be given special consideration since healthy childhood is a prerequisite to normal physical and psychological maturation.
• Prevention of Obesity in Teenagers This paper aims to create an education plan for teenage patients and their parents to effectively inform them and help them avoid obesity.
• Childhood Obesity and Socio-Ecological Model Childhood obesity can be significantly reduced through a public health intervention grounded in the socio-ecological model.
• Childhood Obesity: Causes and Effects Childhood obesity has many causes and effects, which denotes that parents and teachers should make children with obesity engage in regular physical exercise in school and at home.
• Nature vs. Nurture: Child Obesity On the basis of the given assessment, it is evident that a child’s environment is a stronger influencer than his or her genetic makeup
• Childhood Obesity and Public Policies in England The study identifies the preventive measures of the English government to deal with childhood obesity and compares the trends in England with the rest of the UK.
• Obesity Education Plan for Older Adults The given paper presents an obesity education plan targeted at adults and older adults who are overweight or obese and, therefore, are at risk of developing various diseases.
• Obesity in Miami-Dade Children and Adults The problem of childhood obesity is rather dangerous and may produce a short-term and long-term effect on young patients’ social, emotional, and physical health.
• Obesity as a Global Health Issue The purpose of this research is to identify obesity as a global health issue, evaluate the methods and findings conducted on obesity, and find solutions to reduce obesity globally.
• Obesity in Adolescence as a Social Problem The paper states that adolescence is one of the most crucial developmental phases of human life during which the issue of obesity must be solved.
• The Effects of Gender on Child Obesity The high percentage of women’s obesity prevalence is a result of poor nutrition in childhood and access to greater resources in adulthood.
• Obesity Prevention in Community: Strategic Plan This paper is a plan of how to change the way the community should treat obesity and improve people’s health through the required number of interventions.
• Childhood Obesity Prevention: The Role of Nursing Education Nurse practitioners have to deal with childhood obesity challenges and identity healthy physical and environmental factors to help pediatric patients and their parents.
• Childhood Obesity: Methods and Data Collection The first instrument that will be used in data collection is body mass index (BMI). The BMI is measured by dividing a patient’s weight in kilograms by height in meters squared.
• Childhood Obesity Prevention: Physical Education and Nutrition The paper examines how physical education in schools can prevent child obesity and how to educate parents about the importance of proper nutrition.
• Technological Progress as the Cause of Obesity Obesity is the increase of the body’s weight over the natural limit because of accumulated fats. Technology is a cost to the lost creativity and control over the required healthy lifestyle.
• Obesity: Causes, Consequences, and Care Nowadays, an increasing number of people suffer from having excess weight. This paper analyzes the relationship between obesity and other diseases.
• Obesity in the World: the Prevalence, Its Effects to Human Health, and Causes There are various causes of obesity ranging from the quantity of food ingested to the last of physical exercises that utilize the accumulated energy.
• Link Between Watching Television and Obesity One of the primary causes of obesity is a sedentary lifestyle, which often includes excessive screen-watching periods.
• Obesity Problem in the United States Obesity is not just people going fat; it is a disease that causes maladies like type-2 diabetes, heart disease, cancer and strokes.
• Obesity Management: Hypothesis Test Study This paper will show how a hypothesis test study can help inform evidence-based practice regarding obesity management.
• Childhood Obesity: Research Methodology Based on their body mass index measurement or diagnosis by a qualified physician, all children in the sample should be qualified as having obesity.
• Childhood Obesity and Public Health Intervention Childhood obesity can be significantly reduced through a public health intervention grounded in the socio-ecological model, in particular, parents’ active participation.
• Treat and Reduce Obesity Act and Its Potential The paper discusses the background, processing, and potential consequences of a Congress bill presented as H.R.1953: Treat and Reduce Obesity Act of 2017.
• Ways of Treating Obesity in Older Patients The researching obesity management and treatment in older adults is important, as it could help to raise the quality of life of the elderly.
• Obesity Interventions and Nursing Contributions Detecting health problems that may affect children later in their adulthood is worthwhile. This paper reviews roles of nurses’ actions in replacing obesity with wellness.
• Evidence Based Practice Related to Patient Obesity An effective weight management plan should be designed to tackle the health problem. The plan should also be implemented using desirable processes.
• Prevention of Obesity in Children The aim of the study is to find out whether the education of parent on a healthy lifestyle for the children compared with medication treatment, increase the outcome and prevention of obesity.
• Nutrition: Fighting the Childhood Obesity Epidemic Childhood obesity is defined variably as the condition of excessive body fat in children that adversely his/her health. It has been cited as a serious health concern issue in many countries.
• Obesity and Iron Deficiency Among College Students The study seeks to establish the relationship between obesity and iron deficiency by analyzing the serum hepcidin concentration among individuals aged between 19 to 29 years.
• Obesity: Racial and Ethnicity Disparities in West Virginia Numerous social, economic, and environmental factors contribute to racial disparities in obesity. The rates of obesity vary depending on race and ethnicity in West Virginia.
• Health Psychology and Activists’ Views on Obesity This paper examines obesity from the psychological and activists’ perspectives while highlighting some of the steps to be taken in the prevention and curbing of the disease.
• Childhood Obesity: Problem Analysis The introduced project addresses childhood obesity problem and highlights the inconsistency between the existing programs and their implementation in real life.
• Adolescent Obesity: Theories and Interventions This paper explores the issue of adolescent obesity and provides a cohesive action plan to propose how to remedy barriers to the success of implemented interventions.
• Childhood Obesity Interventions: Data Analysis The described analysis of research variables will make it possible to test the research and null hypotheses and contribute to the treatment of obesity in children.
• Obesity in School-Aged Children as a Social Burden In addition to personal concerns, overweight and obese children are at risk for long-term health consequences, including cardiovascular problems and additional comorbidities.
• Obesity Counteractions in Clark County, Washington The prevalence of obesity has been increasing sharply among children and adults in the Clark County because of the failure to observe healthy eating habits.
• Childhood Obesity Causes: Junk Food and Video Games The problem of “competitive foods and beverages” that are sold in schools outside the existing breakfast and lunch programs has been discussed for a while now.
• Advocacy Campaign: Childhood Obesity This paper will review two articles studying different advocacy campaigns: a community-based approach and a youth-led intervention for childhood obesity.
• Obesity as American Social Health Issue In the public health sector, obesity is defined as a social problem because it is associated with the eating habits and bodily lifestyles of every community.
• Childhood Obesity: A Global Public Health Crisis Karnik and Kanekar try to show the threatening tendency towards the deterioration of children`s health and the actions that should be performed to change the situation.
• Food Ads Ban for Childhood Obesity Prevention In order to prevent childhood obesity, it is necessary to ban food ads because they have adverse effects on children’s food preferences, consumption, and purchasing behaviors.
• Obesity in African Americans: Prevention and Therapy According to the official statistics, African American people present the group of American citizens which is the most susceptible to obesity.
• Food Allergies and Obesity This short research paper will examine how food allergies can lead to food addiction that can cause obesity in individuals suffering from these allergies.
• Childhood Obesity and Overweight Issues The paper discusses childhood obesity. It has been shown to have a negative influence on both physical health and mental well-being.
• Discussion of Freedman’s Article “How Junk Food Can End Obesity” David Freedman, in article “How Junk Food Can End Obesity”, talks about various misconceptions regarding healthy food that are common in society.
• Eating Fast Food and Obesity Correlation Analysis The proposed study will attempt to answer the question of what is the relationship between eating fast food and obesity, using correlation analysis.
• Childhood Obesity as an International Problem This paper explores the significance of using the web-based technological approach in combating obesity among Jewish children.
• Depression and Other Antecedents of Obesity Defeating the inertia about taking up a regular programme of sports and exercise can be a challenging goal. Hence, more advocacy campaigns focus on doing something about obesity with a more prudent diet.
• Childhood Obesity Study: Literature Review Obesity in children remains a major public health issue. A growing body of evidence suggests that social networks present a viable way to improve the situation.
• Childhood Obesity and Self-Care Deficit Theory To help the target audience develop an understanding of the effects that their eating behavior has on their health, Dorothea Orem’s Theory of Self-Care Deficit can be utilized.
• Should fast-food restaurants be liable for increasing obesity rates?
• Does public education on healthy eating reduce obesity prevalence?
• Is obesity a result of personal choices or socioeconomic circumstances?
• Should the government impose taxes on soda and junk food?
• Weight loss surgery for obesity: pros and cons.
• Should restaurants be required to display the caloric content of every menu item?
• Genetics and the environment: which is a more significant contributor to obesity?
• Should parents be held accountable for their children’s obesity?
• Does weight stigmatization affect obesity treatment outcomes?
• Does the fashion industry contribute to obesity among women?
• Childhood Obesity: Data Management The use of electronic health records (EHR) is regarded as one of the effective ways to treat obesity in the population.
• Childhood Obesity Problem Solution As a means of solving the problem of childhood obesity, the author of the research proposes to develop healthy custom menus for schools under a program called “Soul Food.”
• Childhood Obesity, Social Actions and Intervention This literature review presents the major social actions and family-based interventions that have been in use to address the problem of obesity in children.
• Obesity: High Accumulation of Adipose Tissue It is important to point out that obesity is a complex and intricate disease that is associated with a host of different metabolic illnesses.
• Childhood Obesity During the COVID-19 Pandemic While the COVID-19 pandemic elicited one of the worst prevalences of childhood obesity, determining its extent was a problem due to the lockdown.
• Overweight and Obesity Prevalence in the US Obesity is a significant public health problem recognized as one of the leading causes of mortality in the United States. Obesity and overweight are two common disorders.
• Obesity Screening Training Using the 5AS Framework The paper aims to decrease obesity levels at the community level. It provides the PCPs with the tools that would allow them to identify patients.
• Prevalence and Control of Obesity in Texas Obesity has been a severe health issue in the United States and globally. A person is obese if their size is more significant than the average weight.
• Nutrition: Obesity Pandemic and Genetic Code The environment in which we access the food we consume has changed. Unhealthy foods are cheaper, and there is no motivation to eat healthily.
• Preventing Obesity Health Issues From Childhood The selected problem is childhood obesity, the rates of which increase nationwide yearly and require the attention of the government, society, and parents.
• Describing the Problem of Childhood Obesity Childhood obesity is a problem that affects many children. If individuals experience a health issue in their childhood, it is going to lead to negative consequences.
• Researching of Obesity in Florida It is important to note that Florida does not elicit the only state with an obesity problem, as the nation’s obesity prevalence stood at 42.4% in 2018.
• Preventing Obesity Health Issues From the Childhood The paper is valuable for parents of children who are subject to gaining excess weight because the report offers how to solve the issue.
• The Social Problem of Obesity in Adolescence The social worker should be the bridge uniting obese individuals and society advertising social changes, and ending injustice and discrimination.
• Obesity and Health Outcomes in COVID-19 Patients The COVID-19 pandemic has posed many challenges over the last three years, and significant research has been done regarding its health effects and factors.
• Childhood Obesity in the US from Economic Perspective The economic explanation for the problem of childhood obesity refers to the inability of a part of the population to provide themselves and their children with healthy food.
• Obesity in the United States of America The article discusses the causes of the obesity pandemic in the United States of America, which has been recognized as a pandemic due to its scope, and high prevalence.
• The Problem of Childhood Obesity Obesity in childhood is a great concern of current medicine as the habits of healthy eating and lifestyle are taught by parents at an early age.
• Oral Health and Obesity Among Adolescents This research paper developed the idea of using dental offices as the primary gateway to detect potential obesity among Texas adolescents.
• Obesity, Weight Loss Programs and Nutrition The article addresses issues that can help increase access to information related to the provision of weight loss programs and nutrition.
• Childhood Obesity in the US From an Economic Perspective Looking at the problem of childhood obesity from an economic point of view offers an understanding of a wider range of causes and the definition of government intervention.
• Diet, Physical Activity, Obesity and Related Cancer Risk The paper addresses the connection between cancer and physical activity, diet, and obesity in Latin America and the USA. The transitions in dietary practices may be observed.
• Obesity From Sociological Imagination Viewpoint Most obese individuals understand that the modern market is not ready to accept them due to negative sociological imagination.
• The Current Problem of Obesity in the United States The paper raises the current problem of obesity in the United States and informs people about the issue, as well as what effect obesity can have on health.
• Childhood and Adolescent Obesity and Its Reasons Various socio-economic, health-related, biological, and behavioral factors may cause childhood obesity. They include an unhealthy diet and insufficient physical activity and sleep.
• Pediatric Obesity and Its Treatment Pediatric obesity is often the result of unhealthy nutrition and the lack of control from parents but not of health issues or hormonal imbalance.
• Impact of Obesity on Healthcare System Patients suffering from obesity suffer immensely from stigma during the process of care due to avoidance which ultimately affects the quality of care.
• Trending Diets to Curb Obesity There are many trending diets that have significant effects on shedding pounds; however, the discourse will focus on the Mediterranean diet.
• Issues of Obesity and Food Addiction Obesity and food addiction have become widespread and significant problems in modern society, both health-related and social.
• Diet, Physical Activity, Obesity, and Related Cancer Risk One’s health is affected by their lifestyle, which should be well managed since childhood to set a basis for a healthier adulthood.
• Articles About Childhood Obesity The most straightforward technique to diagnose childhood obesity is to measure the child’s weight and height and compare them to conventional height and weight charts.
• Obesity Prevention Policy Making in Texas Obesity is a national health problem, especially in Texas; therefore, the state immediately needed to launch a policy to combat and prevent obesity in the population.
• Obesity and How It Can Cause Chronic Diseases Obesity is associated with increased cardiovascular diseases, and cancer risks. The modifications in nutrition patterns and physical activity are effective methods to manage them.
• Physical Wellness to Prevent Obesity Heart Diseases Heart disease remains to be one of the most severe health concerns around the world. One of the leading causes of the condition is obesity.
• Obesity and General State of Public Health Obesity is a condition caused by an abnormal or excessive buildup of fat that poses a health concern. It raises the risk of developing various diseases and health issues.
• Ways of Obesity Interventions The paper discusses ways of obesity interventions. It includes diet and exercise, patient education, adherence to medication, and social justice.
• Obesity, Cardiovascular and Inflammatory Condition Under Hormones The essay discusses heart-related diseases and obesity conditions in the human body. The essay also explains the ghrelin hormone and how it affects the cardiovascular system.
• Aspects of Obesity Risk Factors Obesity is one of the most pressing concerns in recent years. Most studies attribute the rising cases of obesity to economic development.
• Obesity in Adolescence in the Hispanic Community The health risks linked to Hispanic community adolescent obesity range from diabetes, heart problems, sleep disorders, asthma, and joint pain.
• Obesity as a Wellness Concern in the Nursing Field A critical analysis of wellness can provide an understanding of why people make specific health-related choices.
• The link between excess weight and chronic diseases.
• The role of genetics in obesity.
• The impact on income and education on obesity risks.
• The influence of food advertising on consumer choices.
• Debunking the myths related to weight loss.
• Obesity during pregnancy: risks and complications.
• Cultural influences on eating patterns and obesity prevalence.
• Community initiatives for obesity prevention.
• The healthcare and societal costs of obesity.
• The bidirectional relationship between sleep disorders and obesity.
• Physio- and Psychological Causes of Obesity The paper states that obesity is a complex problem in the formation of which many physiological and psychological factors are involved.
• How Junk Diets Can Reduce Obesity To control obesity there is a need to ensure that the junk foods produced are safe for consumption before being released into the foods market.
• The Problem of Obesity: Weight Management Obesity is now a significant public health issue around the world. The type 2 diabetes, cardiac conditions, stroke, and metabolism are the main risk factors.
• Behavioral Modifications for Patients With Obesity This paper aims to find out in obese patients, do lifestyle and behavioral changes, compared to weight loss surgery, improve patients’ health and reduce complications.
• Sleep Deprivation Effects on Adolescents Who Suffer From Obesity The academic literature on sleep deprivation argues that it has a number of adverse health effects on children and adolescents, with obesity being one of them.
• Hypertensive Patients Will Maintain Healthy Blood Pressure and Prevent Obesity Despite hypertension and obesity are being major life threats, there are safer lifeways that one can use to combat the problem.
• The Consequences of Obesity: An Annotated Bibliography To review the literature data, the authors searched for corresponding articles on the PubMed database using specific keywords.
• Evolving Societal Norms of Obesity The primary individual factors that lead to overeating include limited self-control, peer pressure, and automatic functioning.
• The Worldwide Health Problem: Obesity in Children The paper touch upon the main causes of obesity, its spread throughout the world, the major effects of the condition and ways of prevention.
• Mental Stability and Obesity Interrelation The study aims to conduct an integrative review synthesizing and interpreting existing research results on the interrelation between mental stability and obesity.
• Crutcho Public School: Obesity in School Children Numerous school children at Crutcho Public elementary school, Oklahoma City, are obese revealing how obesity is a threat to that community.
• A National Childhood Obesity Prevention Program We Can!® A national childhood obesity prevention program We Can!® explains the rules for eating right and getting active. The program also pays attention to reducing screen time.
• Obesity in Low-Income Community: Diet and Physical Activity The research evaluates the relationship between family earnings and physical activity and overweight rates of children in 8 different communities divided by race or ethnicity.
• Dealing with Obesity as a Societal Concern This essay shall discuss the health issue of obesity, a social health problem that is, unfortunately, growing at a rapid rate.
• Adolescent Obesity in the United States The article reflects the problem of overweight in the use, a consideration which the authors blame on influential factors such as age and body mass index.
• Obesity Problem Solved by Proper Nutrition and Exercise Most people who suffer from obesity are often discouraged to pursue nutrition and exercise because their bodies cannot achieve a particular look.
• Girls with Obesity: Hospital-Based Intervention This paper includes a brief description of a hospital-based intervention targeting middle-school girls with obesity.
• Hispanic Obesity in the Context of Cultural Empowerment This paper identifies negative factors directly causing obesity within the Hispanic people while distinguishing positive effects upon which potential interventions should be based.
• Childhood Obesity Teaching Experience and Observations The proposed teaching plan aimed at introducing the importance of healthy eating habits to children between the ages of 6 and 11.
• Care Plan: Quincy Town, Massachusetts With Childhood Obesity This study will develop a community assessment program based on the city with the aim of creating a care plan for tackling the issue of child obesity in the town.
• Exercise for Obesity Description There are numerous methods by which obesity can be controlled and one of the most effective ways is through exercising.
• Obesity and Disparity in African American Women Several studies indicate that the rate of developing obesity is the highest in African American populations in the US.
• Factors Increasing the Risk of Obesity The consumption of fast food or processed products is one of the major factors increasing the risk of obesity and associated health outcomes.
• Obesity, Diabetes and Self-Care The paper discusses being overweight or obese is a high-risk factor for diabetes mellitus and self-care among middle-aged diabetics is a function of education and income.
• Childhood Obesity in Modern Schools Most schools have poor canteens with untrained staff and poor equipment for workers. That’s why they can’t cook quality food and offer better services to students.
• Obesity in Hispanic American Citizens The issue of obesity anong Hispanic Americans occurs as a result of poor dieting choices caused by misinformed perceptions of proper eating.
• Effectiveness of a Diet and Physical Activity on the Prevention of Obesity Research indicates that obesity is the global epidemic of the 21st century, especially due to its prevalent growth and health implications.
• Community Obesity and Diabetes: Mississippi Focus Study The paper provides a detailed discussion of the correct method to be used in the state of Mississippi to control and avoid obesity and diabetes issues.
• Multicausality: Reserpine, Breast Cancer, and Obesity All the factors are not significant in the context of the liability to breast cancer development, though their minor influence is undeniable.
• The Home Food Environment and Obesity-Promoting Eating Behaviours Campbell, Crawford, Salmon, Carver, Garnett, and Baur conducted a study to determine the associations between the home food environment and obesity.
• The Problem of Childhood Obesity in the United States Childhood obesity is one of the reasons for the development of chronic diseases. In the US the problem is quite burning as the percentage of obese children increased significantly.
• Children Obesity in the United States Together with other problems and illnesses, obesity stands as one of the main difficulties in modern societies.
• The Situation of Obesity in Children in the U.S. The paper will discuss the situation of obesity in Children in the U.S. while giving the associated outcomes and consequences.
• Childhood Obesity and Healthy Lifestyles The purpose of this paper is to discuss childhood obesity and the various ways of fostering good eating habits and healthy lifestyles.
• Screen Time and Pediatric Obesity Among School-Aged Children Increased screen time raises the likelihood of children becoming overweight/obese because of the deficiency of physical exercise and the consumption of high-calorie foods.
• Policymaker Visit About the Childhood Obesity Problem The policy issue of childhood obesity continues to be burning in American society. It causes a variety of concurrent problems including mental disorders.
• Public Health Interventions and Economics: Obesity The purpose of this article is to consider the economic feasibility of public health interventions to prevent the emergence of the problem of obesity.
• Obesity Overview and Ways to Improve Health The main focus of this paper is to analyze the problems of vice marketing and some unhealthy products to teens and children.
• Nursing: Issue of Obesity, Impact of Food Obesity is a pandemic problem in America. The fast food industry is under pressure from critics about the Americans weight gain problem.
• Childhood Overweight and Obesity Childhood overweight and obesity have increased in the US. Effective transportation systems and planning decisions could eliminate such overweight-related challenges.
• Obesity Negative Influence on Public Health
• Problematic of Obesity in Mexican Americans
• Child Obesity Problem in the United States
• Obesity Rates and Global Economy
• Screen Time and Pediatric Obesity in School-Aged Children
• Obesity: Cause and Treatment
• Obesity Treatment – More Than Food
• Effects of Exercise on Obesity Reduction in Adults
• The Problem of Obesity in the Latin Community
• Obesity Prevention in Ramsey County, Minnesota
• Childhood Obesity and Its Potential Prevention
• Non-Surgical Reduction of Obesity and Overweight in Young Adults
• Obesity Prevention Due to Education
• Physical Activity and Obesity in Children by Hills et al.
• The Best Way to Address Obesity in the United States
• Nursing Diabetes and Obesity Patients
• Obesity Problem Description and Analysis
• The Issues with Obesity of Children and Adolescents
• Obesity in People with Intellectual Disabilities’: The Article Review
• Non-Surgical Reduction of Obesity in Young Adults
• Obesity in Children in the United States
• Childhood Obesity in Ocean Springs Mississippi
• The Problem of Children Obesity
• “Physical Activity and Obesity in Children” by A. P. Hills
• “Physical Activity and Obesity in Children” by Hills
• The Current State of Obesity in Children Issue
• Effects of Obesity on Human Lifespan Development
• Obesity and High Blood Pressure as Health Issues
• Adult Obesity: Treatment Program
• Obesity in Children and Their Physical Activity
• The Prevention of Childhood Obesity in Children of 1 to 10 Years of Age
• Obesity as a Major Health Concern in the United States
• Screen Time and Pediatric Obesity
• Technology as the Cause of Obesity
• Janet Tomiyama’s “Stress and Obesity” Summary
• A Dissemination Plan on Adolescent Obesity and Falls in Elderly Population
• The Issue of Obesity: Reasons and Consequences
• “Obesity and the Growing Brain” by Stacy Lu
• Obesity Disease: Symptoms and Causes
• Obesity Among Mexican-American School-Age Children in the US
• Obesity as a One of the Major Health Concerns
• Obesity: Diet Management in Adult Patients
• Children’s Obesity in the Hispanic Population
• Prevention of Childhood Obesity
• Assessing Inputs and Outputs of a Summer Obesity Prevention Program
• Designing a Program to Address Obesity in Florida
• Widespread Obesity in Low-Income Societies
• Health Policy: Obesity in Children
• Youth Obesity In Clark County in Vancouver Washington
• Obesity in Clark County and Health Policy Proposal
• Obesity: Is It a Disease?
• Clark County Obesity Problem
• Obesity Action Coalition Website Promoting Health
• Childhood Obesity: Medical Complications and Social Problems
• How to Address Obesity in the United States
• The Epidemic of Obesity: Issue Analysis
• Eating Healthy and Its Link to Obesity
• Child Obesity in North America
• Personal Issues: Marriage, Obesity, and Alcohol Abuse
• Obesity in Children: Relevance of School-Based BMI Reporting Policy
• Obesity in the United States: Defining the Problem
• Obesity in Children in the US
• Childhood Obesity: Issue Analysis
• Physical Exercises as Obesity Treatment
• Data Mining Techniques for African American Childhood Obesity Factors
• Approaches to Childhood Obesity Treatment
• Researching Childhood Obesity Issues
• Infant Feeding Practices and Early Childhood Obesity
• Prevalence of Obesity and Severe Obesity in U.S. Children
• Problem of Obesity: Analytic Method
• Obesity as National Practice Problem
• Practice Problem of the Obesity in United States
• Exercise for Obesity Management: Evidence-Based Project
• Obesity in African-American Women: Methodology
• The Epidemiology of Obesity
• Pediatric Obesity Study Methodology
• Adult Obesity Causes & Consequences
• Community Health: Obesity Prevention
• Obesity Treatment in Primary Care: Evidence-Based Guide
• Childhood Obesity and Mothers’ Education Project
• Childhood Obesity Research Critiques
• Childhood Obesity: Medication and Parent Education
• Obesity Caused by Fast-Food as a Nursing Practice Issue
• Cardiometabolic Response to Obesity Treatment
• Motivational Interviewing in Obesity Reduction: Statistical Analysis
• Obesity Among the Adult Population: Research Planning
• Research and Global Health: Obesity and Overweight
• Childhood Obesity as a Topic for Academic Studies
• Adolescent Obesity Treatment in Primary Care
• The Issues of Childhood Obesity: Overweight and Parent Education
• Childhood Obesity and Parent Education: Ethical Issues
• Obesity Reduction and Effectiveness of Interventions
• Childhood and Adult Obesity in the US in 2011-12
• Anti-Obesity Project’s Sponsors in the USA
• Obesity Prevention Advocacy Campaigns
• Childhood Obesity Study, Ethics, and Human Rights
• Childhood Obesity, Demographics and Environment
• Overweight and Obesity in 195 Countries Since 1980
• Childhood Obesity and American Policy Intervention
• Obesity in Miami as a Policy-Priority Issue
• Efficient Ways to Manage Obesity
• Childhood Obesity and Healtcare Spending in the US
• Childhood Obesity, Medical and Parental Education
• Nursing Role in Tackling Youth Obesity
• Childhood Obesity: Problem Issues
• Adolescent Obesity and Parental Education Study
• Obesity Prevention and Patient Teaching Plan
• “Management of Obesity” by Dietz et al.
• Nutrition and Obesity: Management and Prevention
• Obesity, Diet Modification and Physical Exercises
• Obesity, Its Definition, Treatment and Prevention
• Childhood Obesity and Eating Habits in Low-Income Families
• Diet and Lifestyle vs Surgery in Obesity Treatment
• Obesity: Society’s Attitude and Media Profiling
• Childhood Obesity and Family’s Responsibility
• Childhood Obesity: Parental Education vs. Medicaments
• Childhood Obesity and Healthy Lifestyle Education
• Childhood Obesity and Health Promoting Schools Program
• Childhood Obesity Risks, Reasons, Prevention
• Fast Food as a Cause of Obesity in the US and World
• Obesity Prevention and Education in Young Children
• Childhood Obesity: The Relationships Between Overweight and Parental Education
• Obesity, Its Demographics and Health Effects
• Obesity Treatment: Surgery vs. Diet and Exercises
• Child Obesity as London’s Urban Health Issue
• Obesity Prevention in Young Children: Evidence-Based Project
• Prevalence of Childhood and Adult Obesity in the US
• The Role of Nurses in the Obesity Problem
• The Issue of Obesity in Youth in the U.S.
• The Role of Family in Childhood Obesity
• Obesity Among Children of London Borough of Southwark
• Childhood Obesity Risks and Preventive Measures
• Life Expectancy and Obesity Health Indicators
• The Overuse of Antibiotics and Its Role in Child Obesity
• Children and Adolescents With Obesity: Physical Examination
• Obesity in the United States: Learning Process
• Pharmacotherapy for Childhood Obesity
• “Let’s Move” Intervention for Childhood Obesity
• Obesity Prevention in Childhood
• Patient Education for Obesity Treatment
• Childhood Obesity Prevention Trends
• Obesity Prevention in Young Children in US
• Wellness, Academics & You: Obesity Intervention
• Childhood Obesity, Health and Psychological State
• Parents’ Education in Childhood Obesity Prevention
• Childhood Obesity in the US
• Childhood Obesity and Its Solutions
• Betty Neuman’s System Model for Adult Obesity
• Obesity Problem among the Adult Population
• Obesity Education in Social Media for Children
• Childhood Obesity and Governmental Measures
• Childhood Obesity Research and Ethical Concerns
• Obesity, Its Contributing Factors and Consequences
• Obesity among the Adult Population
• Multimodal-Lifestyle Intervention for Obesity
• Technological Education Programs and Obesity Prevention
• Childhood Obesity and Independent Variable in Parents
• Childhood Obesity, Its Definition and Causes
• Public Health Initiative for Childhood Obesity
• Childhood Obesity in the US: Factors and Challenges
• Obesity: Genetic, Hormonal and Environmental Influences
• The Problem of Obesity in the USA
• Childhood Obesity in the USA
• Racial and Ethnic Trends in Childhood Obesity in the US
• Diabetic Patients with Obesity or Overweight
• Age and Gender in Childhood Obesity Prevention
• Childhood Obesity and Public Health Interventions
• Obesity in Florida and Prevention Programs
• Obesity in Afro-Americans: Ethics of Intervention
• Helping Children with Obesity and Health Risks
• The Role of Nurses in the Problem of Obesity
• Healthy Nutrition: Obesity Prevention in Young Children
• Myocardial Infarction, Obesity and Hypertension
• Childhood Obesity and Parent Education
• Obesity’s Effect on Children and Elderly People
• Childhood Obesity and Community Nursing Intervention
• Obesity Trends Among Non-Hispanic Whites and Blacks
• Family-Based Childhood Obesity and Parental Weight
• Childhood Obesity and Depression Intervention
• Problem of the Childhood Obesity
• Advocacy Campaign: the Problem of Childhood Obesity
• Humanistic Theory in Childhood Obesity Research
• Childhood Obesity and Control Measures in the US
• Decreasing Obesity in Jewish Children
• Nutrition: Obesity Epidemics in America
• Fast Food and Obesity Link – Nutrition
• Dairy Products Consumption and Obesity – Nutrition
• Nutrition Issues: Obesity and Breastfeeding
• The Evidence of Association between Iron Deficiency and Childhood Obesity
• Childhood Obesity: a Population Health Issue
• What Factors Causes Obesity?
• What Are Five Problems With Obesity?
• Can the Government Help the Obesity Issue?
• What Are the Three Dangers of Obesity?
• What Are Ten Health Problems Associated With Obesity?
• Are the Parents to Blame for Childhood Obesity?
• What Are the Social Effects of Obesity?
• Does Adolescent Media Use Cause Obesity and Eating Disorders?
• How Is Obesity Affecting the World?
• How Does Obesity Impact Quality of Life?
• Does Society Affect America’s Obesity Crisis?
• How Does Obesity Affect You Mentally?
• How Does Obesity Impact Children?
• How Does Obesity Affect Self-Esteem?
• How Does Obesity Cause Depression?
• Are First Generation Mexican Children More Prone to Obesity Than Their Second Generation Counterparts?
• Should Fast Food Companies Be Held Responsibility for Children’s Obesity?
• Does Obesity Cause Mood Swings?
• What Are the Causes and Effects of Childhood Obesity?
• Is Obesity a Mental or Physical Illness?
• What Comes First: Depression or Obesity?
• What Makes Obesity Dangerous?
• Which European Country Has the Highest Rate of Obesity?
• What Is the Obesity Rate in Africa?

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• Published: 18 July 2018

Epidemiology and Population Health

How has big data contributed to obesity research? A review of the literature

• Kate A. Timmins   ORCID: orcid.org/0000-0002-7643-7319 1 ,
• Mark A. Green 2 ,
• Duncan Radley 3 ,
• Michelle A. Morris   ORCID: orcid.org/0000-0002-9325-619X 4 &
• Jamie Pearce 5  

International Journal of Obesity volume  42 ,  pages 1951–1962 ( 2018 ) Cite this article

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There has been growing interest in the potential of ‘big data’ to enhance our understanding in medicine and public health. Although there is no agreed definition of big data, accepted critical components include greater volume, complexity, coverage and speed of availability. Much of these data are ‘found’ (as opposed to ‘made’), in that they have been collected for non-research purposes, but could include valuable information for research. The aim of this paper is to review the contribution of ‘found’ data to obesity research to date, and describe the benefits and challenges encountered. A narrative review was conducted to identify and collate peer-reviewed research studies. Database searches conducted up to September 2017 found original studies using a variety of data types and sources. These included: retail sales, transport, geospatial, commercial weight management data, social media, and smartphones and wearable technologies. The narrative review highlights the variety of data uses in the literature: describing the built environment, exploring social networks, estimating nutrient purchases or assessing the impact of interventions. The examples demonstrate four significant ways in which ‘found’ data can complement conventional ‘made’ data: firstly, in moving beyond constraints in scope (coverage, size and temporality); secondly, in providing objective, quantitative measures; thirdly, in reaching hard-to-access population groups; and lastly in the potential for evaluating real-world interventions. Alongside these opportunities, ‘found’ data come with distinct challenges, such as: ethical and legal questions around access and ownership; commercial sensitivities; costs; lack of control over data acquisition; validity; representativeness; finding appropriate comparators; and complexities of data processing, management and linkage. Despite widespread recognition of the opportunities, the impact of ‘found’ data on academic obesity research has been limited. The merit of such data lies not in their novelty, but in the benefits they could add over and above, or in combination with, conventionally collected data.

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Introduction.

There has been growing interest in the potential of ‘big data’ for enhancing our understanding of a wide array of societal challenges including in medicine and public health. Facilitated by advances in computing hardware, software and networking, big data have been heralded as a powerful new resource that can provide novel insights into human behaviour and social phenomena. Despite the broad excitement and interest, there is no single agreed definition of big data. However, it is widely accepted that the greater volume, complexity, coverage and speed of availability of the observations and variables are critical components [ 1 , 2 ]. In contrast, conventional, or ‘small’, data (e.g. from trials, cohorts or surveys), tend to be produced in more constrained ways using sampling strategies that restrict the scope (e.g. number of questions), size (e.g. number of respondents) or temporality (e.g. number of time points).

Big data generation tends to strive to: be comprehensive, often capturing full populations; have high temporal and/or spatial resolution; be interlinked and connected across different data resources with common fields to enable unique identification; and be dynamic and adaptive to allow new and greater quantities of data to be readily appended [ 3 ]. Connelly et al. [ 2 ] make the useful distinction between data that are ‘made’ and that which are ‘found’. ‘Made’ data include information collected to investigate a defined hypotheses; whereas ‘found’ data have been collected for alternative (often non-research) purposes, but could include potentially valuable information for research. The sources and production of ‘found’ data include, but are not limited to, online activities (e.g. social media, web searches), commercial transactions (e.g. in-store purchase from supermarkets or bank transactions), remote physiological sensors (e.g. heart-rate monitors) or environmental sensors (e.g. GPS, satellite data).

With increasing volumes and greater access to data in electronic formats, it is unsurprising that researchers are beginning to apply big data to key concerns including mental health [ 4 ], infectious disease [ 5 ] and healthcare [ 6 ]. In the field of obesity research, there is a long history of using routine data sources to track the prevalence of the disease, as well as identify risk factors. Supplementing this with new forms of data has potential to broaden our understanding of obesity, bringing together information from different facets of environment and behaviours. Although obtaining, analysing and disseminating big data has potential to benefit society, there are also a number of possible risks [ 3 , 7 ], including challenges relating to data governance and methodological robustness. There has not yet been an attempt to review the current applications of big data to obesity-related research.

The aim of this paper is to review the contribution of ‘found’ data (adopting Connelley et al’s distinction) to obesity research, and consider the implications for the future of big data in this field. We focus on data that have been repurposed for research, rather than data originally designed for research or health monitoring purposes (such as health register or birth cohorts), because these sources of data offer new opportunities and challenges compared to conventional ‘made’ research data. Our intention is to review the nature and scope of the research that is emerging, and describe the benefits and challenges encountered.

The aim of this review was illustrative, rather than to provide an exhaustive examination of obesity research examples. We developed a narrative, rather than systematic, review that identifies and collates research in which ‘found’ data have been adopted to address obesity-related concerns. From a scoping of the literature in November 2016, informed by activities within the ESRC Strategic Network for Obesity meetings (reference pending), we identified six categories of data: retail sales, transport, geospatial, commercial weight management data, social media, and smartphones and wearable technologies. These data categories are described in the Results.

Database searches were conducted between January and April 2017 (MEDLINE, PsycINFO, SPORTDiscus) using search terms such as: obesity, diet*, physical activity, body mass index, big data, commercial data, loyalty card, smart ticket, smart metr*, point of sale, tax*, purchas*, social media, crowd sourc*, app, mobile phone, cell phone. We only considered articles published in English in peer-reviewed academic literature, which described original research, and that used data sets not originally intended for research purposes. Outcomes considered relevant included measures of obesity, as well as dietary or physical activity outcomes. Search updates were run in September 2017, and articles were also found through citations and expert recommendation.

For each data category, we collated details from relevant studies to describe the data used, how and why they had been used, and the benefits and limitations of using them. We then considered as a whole the extent to which these data had contributed to obesity research to date.

An overview of the examples found in the literature can be seen in Table  1 , including a brief summary of the added value and limitations of each data type. These are described in more detail below.

Retail sales data

What are the data.

Perhaps the earliest usage of ‘found’ data for obesity research involves the examination of retail sales data. Product sales data have long been collected by retailers to monitor transactions. Data can be taken directly from barcode scanners [ 8 , 9 ], consumer marketing panels [ 10 ], retailer data sets [ 11 , 12 , 13 , 14 , 15 ] or national-level industry data [ 16 , 17 ]. More recently, these data have been linked to individual-level information (e.g. age, sex, address) using store loyalty cards [ 18 ].

What has the data been used for?

Published studies have had varied purposes: monitoring nutrient or food intakes at a population level [ 8 , 16 , 17 ], ascertaining national or regional nutrient availability [ 19 ], comparing ‘vice’ purchases online versus in store [ 15 ], or evaluating the impact of policies or interventions (e.g. changes to benefits (food stamps) [ 12 ], nutrition labelling [ 20 ], taxation [ 10 , 14 ] or public health campaigns [ 13 ]). Some studies have looked at the association between sales and aggregate-level outcomes (e.g. national-level BMI estimates [ 16 , 17 ]), or examined longitudinal patterns in sales [ 10 , 13 , 14 ].

What do they add over and above conventional data?

There appear to be three motivations for using this type of data: wide coverage (e.g. population level [ 16 , 17 ]); high ecological validity [ 14 , 15 ] and benefits of automation [ 8 , 21 ]. Conventional dietary assessment is often criticised as: burdensome, reliant on self-reports, expensive and typically only practical for use during a short window of time. Automatically collected sales data could reduce both respondent [ 22 ] and researcher [ 21 ] burden, and potentially minimise self-report errors [ 9 , 19 , 21 ]. Automation should also be considerably more cost-effective [ 8 , 9 , 11 , 21 , 22 ], enabling the collection of longitudinal and more timely data.

Sales data may be particularly useful for quasi-experimental evaluations of policy, where conventional randomised controlled trials (RCTs) may not be possible, and timely, longitudinal data are crucial. For example: Nikolova et al. [ 20 ] investigated the effect of point-of-sale nutritional information on consumer behaviour; Andreyeva et al [ 12 ] assessed the impact on nutrient purchases following revisions to federal food provision in the US; Colchero et al. [ 10 ] monitored panel members’ drinks purchases before and after the introduction of a tax on sugar-sweetened beverages in Mexico; Schwartz et al. [ 13 ] examined supermarket sales of sugary drinks before and during a campaign to reduce consumption and compared sales to those outside the community; and Silver et al. [ 14 ] looked at the impact of a tax on sugar-sweetened beverage consumption before and after a tax was implemented in Berkeley, California.

What are the limitations?

All studies identified issues in coverage, as they were only able to access data from certain supermarket chains [ 13 , 14 ] or panels, which were not representative [ 10 ]. In addition, purchases of food and drinks do not necessarily equate to dietary consumption [ 8 , 12 , 22 ]. Furthermore, no studies have yet been able to link to individual-level health outcomes. Several authors also described problems with the quality of the data, for example, missing data due to technical faults or inconsistencies in recording [ 9 , 14 , 19 , 21 ]. This is compounded by the dynamic nature of the retail food market [ 21 , 22 ]. Data linkage was one of the main challenges identified in this type of study.

Quasi-experimental studies, whilst high in ecological validity, are unable to isolate the causal mechanism given the many potential confounders, and researchers struggle to find appropriate comparison data; some studies compared to counterfactual data (i.e. consumption predicted on the basis of pre-tax trends), which come with a number of assumptions [ 10 , 14 ] and do not generate results demonstrating causal relationships.

A final challenge identified is the relationship with commercial partners. There is a concern that these data sets may prove cost-prohibitive for research purposes [ 22 ], and that their use may be restricted by non-disclosure agreements [ 22 ] or confidentiality worries [ 19 ]. Difficulties initiating partnerships or with finding partners with appropriate data collection were also described [ 14 ].

Transport monitoring has long involved the collection of data on mode and volume of transport to aid in planning and infrastructure. Collection of transport data is increasingly sophisticated and new technologies can offer novel insights into travel and lifestyle behaviour as well. For example, on-board sensors within vehicles to monitor vehicle performance can provide data on travel patterns. External sensors along transport networks such as roads or public transport are also increasingly more common both for monitoring transport flows and in the fields of urban informatics. The popularity of smart card systems for public transport systems also presents an opportunity for obtaining information on destinations, routes and transport modes, and may include additional information about individuals such as socio-demographic characteristics.

What have the data been used for?

There were few applications utilising such data within obesity-related research. Some studies have used aggregated data sources to explore patterns associated with obesity. For example, Lopez-Zetina et al. [ 23 ] used data collected from the ‘Highway Performance Monitoring System’ on traffic flow data for public roadways in the US to investigate the ecological association between areas with greater motorised transport usage (vehicle miles of travel) and obesity prevalence. US driver licence data have also been proposed as a potentially useful opportunity as they contain information on height and weight [ 24 ]. Other applications have compared the impacts from the introduction of city-based bicycle hire schemes, by analysing usage data from cycle hire stations [ 25 ]. Some studies have also used these data as inputs to simulation models to estimate the impacts on health outcomes [ 26 , 27 ].

Transport data often include explicit information about spatial location. We know little about the activity spaces and environments that individuals engage within their daily lives and these data can illuminate the role of urban structure, utilisation of services, or engagement with green space. Conventional research exploring their associations with obesity tend to rely on simple approximations of these concepts, whereas new forms of data can provide a more valid and objective picture of exposure. They additionally present greater detail on how individuals are engaging with different modes of transport. The rise of private motorised transport has been touted as one important driver of obesity trends [ 23 ]. These data can therefore help to improve our understanding of physical activity from transport options that conventional data are unable to cover.

A key criticism is that many data sources only contain journey information, with little additional information about lifestyle behaviours or socio-demographic characteristics. Similar to retail sales data (above), the link between what is measured and the relevant behaviour can only be assumed or extrapolated. For example, knowing that an individual travelled from point A to point B can only inform us about the direction of their travel, and not the impact of travel on physical activity or dietary behaviours, nor the wider impact of an intervention. Data linkage is therefore important to be able to unpick these complex interactions to provide robust explanations for obesity-related behaviour.

Commercial weight management data

This category refers to data that are provided by commercial weight management programmes. Weight management programmes routinely collect data not for research but as a standard part of their service provision. The intended use of the data may vary, possibilities including: client orientated feedback (e.g. self-monitoring), continuous service improvement (e.g. to monitor adaptations to programme content/delivery) and, if the service is being delivered as a procured provision, to monitor contractual targets (e.g. reporting key performance indicators). Data sets are often substantial in terms of participant numbers, and include information on individual characteristics (e.g. socio-demographic factors), engagement with the programme (e.g. enrolment, attrition or service usage) and weight outcomes.

Commercial data provide the opportunity for independent real-world service evaluations. For instance: Ahern et al. [ 28 ] reported outcomes for 29,326 participants attending Weight Watchers NHS Referral Scheme between April 2007 and October 2009; Finley et al. [ 29 ] examined 60,164 men and women, aged 18–79 years, who enrolled in the Jenny Craig Platinum programme between May 2001 and May 2002; Johnson et al. [ 30 ] investigated Nutracheck, a direct-to-consumer Internet weight-loss programme; Stubbs et al. [ 31 ] reported the short-term outcomes of 1,356,105 self-referred, fee-paying adult participants of Slimming World groups joining between January 2010 and April 2012; and Fagg et al. [ 32 ] assessed outcomes associated with participation in a family-based weight management programme (MEND 7–13, Mind, Exercise, Nutrition..Do it!) for childhood overweight in 21,132 referred or self-referred children.

These outcome evaluations provide important insight given that many large-scale programmes being used to treat obesity have not had their effectiveness formally evaluated using recognised research methodologies (e.g. RCTs). Further, even when programmes have been rigorously evaluated under trial conditions, programme effectiveness observed within controlled settings may differ to outcomes in real-world contexts [ 33 , 34 ].

The data also provide the opportunity to consider a variety of research questions that are commonly not addressed within conventional effectiveness trial research designs or are beyond the scope of such evaluations. For instance, the data collected are often substantial in terms of numbers of participants: Fagg et al. [ 32 , 35 ] were able to investigate: who is referred to, who started and who completed a child weight management intervention when delivered at scale; whether the socio-demographic characteristics of children attending the intervention matched those of the eligible population; changes in BMI observed under service conditions with those observed under research conditions; and how outcomes of the intervention varied by participant, family, neighbourhood and programme characteristics—all of which was enabled by the large-scale implementation of the intervention.

The wide-reaching scope of data in terms of participants also could allow investigation into hard-to-reach populations who are typically under-represented in conventional research. For example, Fagg et al. were able to explore patterns in programme usage by ethnicity and socioeconomic status—both of which are important to increase our understanding of health inequalities. Combining with other data sources, such as social media, transport and geospatial data, could present further useful insights, for example, by exploring relationships between the environment and programme outcomes.

Similar to the literature on retail sales data (see above), it is recognised that data accessibility, quality, completeness and representativeness must be addressed. Commercial sensitivities also need to be considered, as do ethical issues surrounding consent for data use and achieving appropriate levels of information security, confidentiality, and privacy, particularly given that individual-level data may be involved.

Geospatial refers to data in which the location of objects across environments are stored with a spatially explicit dimension. They include the location of services (e.g. healthcare facilities, restaurants), the layout of road networks, or features of the built environment (e.g. parks, woodland). Data may be accessed through retail databases, national mapping agencies, satellite technology or web mapping platforms (e.g. Google Maps, OpenStreetMap).

Geospatial data have been used to measure different features of the built and natural environment. Many studies have calculated simple counts of retail locations such as fast food outlets as a measure of exposure. For example, consumer and national agency data sources were used to create open access measures of accessibility to retail opportunities including fast food outlets or leisure services [ 36 ]. Other mapping services such as ‘Google Street View’ [ 37 , 38 ] and remote sensing [ 39 , 40 ] have also been used to develop virtual audits of environmental features which are then correlated to measures of obesity.

Where locational information has been collated using conventional approaches (e.g. field audits, surveys), they are often restricted in multiple ways. Data may be collected separately by locale, resulting in gaps in spatial coverage, discrepancies in the information provided by locale, or a lack of joined-up inclusion of data limiting the ability to undertake national-level analyses. They may appear temporally infrequent, and while annual data may be appropriate, services such as Google Maps can allow finer temporal resolution for nuanced analyses. Conventional data sources may also impose costs or licensing arrangements of use of data or in accessing data.

The main drawback is similar to that identified for transport data (above). Typically, geospatial data are fairly basic containing only the location and type of object. To build up a comprehensive view of how humans interact with these objects, we need to know much more. For example, while identifying the location of fast food outlets is valuable, also important are details on types of food sold, opening hours, business turnover, and the nature of in-store marketing and product placementLinkage of data to other sources may increase their usefulness in obesity research—for example, tracking individuals’ movements within and interactions with the environment using GPS-enabled smartphones (see below).

Social media

Social media are computer-assisted technologies that facilitate the creation of virtual networks connecting individuals and allowing the sharing of information. Their use has grown since the beginning of the twenty-first century and are embedded in the everyday lives of many people with, for example, 63% of UK adults using online social networks daily [ 41 ]. The ways in which individuals interact with these services are stored by their providers and can be made available to researchers.

Twitter data represented the majority of studies utilising social media sources. Twitter is an online platform where users can write and share short posts of (at the time of writing) 140 characters or fewer (and may include geographical location when sent using mobile devices). Unlike other social media platforms, Twitter makes a portion (~1%) of its data freely available. Studies typically focused on using descriptive statistics to examine patterns of what was posted. Some studies used geotagged tweets to produce geographical measures of behaviours including dietary behaviours [ 42 , 43 , 44 ], physical activity [ 44 , 45 ] or happiness/wellbeing [ 42 , 46 ]. These were then correlated with data on obesity rates or the density of fast food outlets. Other examples include using social network analysis to explore how messages about childhood obesity spread between individuals [ 47 ].

Other social media platforms have been less commonly utilised. Facebook data on posts shared and interests followed (identified using ‘likes’) were used as proxies for behaviours and opinions/perceptions surrounding obesity [ 48 , 49 , 50 ]. One study examined correlations between these data and ecological measures of obesity [ 51 ]. Other examples included using Reddit posts to characterise discussions about weight loss [ 52 ], utilisation of fast food outlets using Foresquare and Instagram [ 53 ], Strava data to explore physical activity behaviours [ 54 ] or self-reporting of body weight on an online forum [ 55 ].

With individuals opting to increasingly document their lives through digital platforms, social media data offer the potential to form intricate understandings of opinions, interactions with objects, locations and other individuals [ 56 ]. There is a paucity of data on social networks of individuals, and collecting ‘made’ data on the topic is both intensive and costly. Social media data offer cheaper and more comprehensive data on the issue, which can facilitate more in-depth studies on human interactions (particularly international interactions which are rarely considered). This is important given that it has been previously demonstrated that social networks have important roles in understanding obesity [ 57 ].

Few studies have engaged with the representativeness of social media data. For example, studies using Twitter data are purely describing patterns within Twitter users only, who disproportionately represent younger age groups [ 58 ], or even within just those Twitter users who allow geotagging (estimated at just over 1% [ 59 ]). Moving beyond single platforms will not only improve the generalisability of findings, but also open up opportunities for understanding how individuals engage with the increasing digitalisation of life. Linked to this notion of representativeness, we cannot ignore the increasing proportion of ‘bots’ among social media sites. Bots are automated social media accounts which post content with the aim of mimicking the behaviours of individuals. As such, they may contribute data to research, introducing bias to analyses [ 60 ]. Furthermore, our online personalities may not approximate who we are ‘offline’ [ 61 ].

Smartphones and wearable technologies

Smartphones are increasingly pervasive—estimates suggest almost 70% of US adults owned a smartphone in 2015 [ 62 ]. With ever more sophisticated technology, many smartphones now incorporate a range of sensors and logs that open up opportunities for continuous collection of data in free-living environments. Often used alongside smartphones, linked devices, such as wrist-worn activity monitors or heart-rate monitors (wearable technologies), are used to track a user’s behaviour and are often used to supplement ‘life-logs’. Data may be made available from device or app manufacturers.

Studies have typically used smartphone data to describe physical activity outcomes, such as step counts, GPS movements or logged journeys. In this way, activity patterns have been explored across populations, temporally or spatially [ 63 , 64 , 65 ]. There is some overlap here with geospatial data, where smartphone-integrated GPS can be triangulated with app data to describe the use of neighbourhoods or environments. As many smartphones and apps are widely utilised, the data can be used to make international comparisons, for example, correlating activity levels (using step counts) with national obesity trends [ 66 ]. Smartphone data have also been used to evaluate interventions: Heesch et al. [ 67 ] examine cycling behaviour before and after infrastructure changes. Other uses include assessing the influence of smartphone games on physical activity (Pokémon GO [ 68 , 69 ]), or characterising successful users of a weight-loss app (Lose It! [ 62 ]).

A key advantage of smartphone data is the wide-scale coverage, often international. This enables research that is broad in geographic scope, and large data sets offer additional analytical possibilities by being split into ‘training’ and ‘validation’ subsets [ 62 ]. In addition, where data recording is ‘passive’ and continuous, there is a lower respondent burden than many conventional methods, with potential benefits for participant adherence and longitudinal data collection. Apps which require users to actively log information (i.e. the data are non-passively generated) often include prompts and reminders, and thus may offer similar advantages as recognised for Ecological Momentary Assessment [ 70 ]. Incorporating GPS also allows the collection of geographically specific information. Several authors identified that sampling or inferential issues could be at least partially overcome by triangulating smartphone data with conventional research data to offer reassurances in terms of representativeness and validity.

A key issue is sampling: only those individuals who own a particular app, device or model of smartphone will be included in the data. Furthermore, authors cited concerns about the lack of control on data generation, as participants may not consistently carry their phone with them and switched on [ 64 , 66 ]. Missing data due to technical reasons were also common, for example when signal or battery cut out [ 64 , 71 ]. Smartphones are also unable to capture activities where people are unlikely to have their phone on them, such as contact sports or swimming. Finally, user behaviour may be both measured by and influenced by the smartphone app or wearable device itself, with potential repercussions for the interpretation of findings.

This paper provides an overview of how ‘found’ data have been used in obesity research to date. The narrative review highlights the variety of uses in the literature, with contrasting types of data and varied research questions: from describing the built environment, to exploring social networks, estimating nutrient purchases or assessing the impact of interventions. Importantly, each of the described studies has attempted in some way to use this data to infer behaviours associated with energy balance (diet and physical activity) or to understand the context in which obesity-related behavioural decisions are made. In the ensuing discussion, we offer a summary of the opportunities highlighted by the literature. The intention is to illustrate areas of interest and promise, rather than attempt a full critical evaluation of the use of data in these studies.

Opportunities for big data research

The examples identified in this review demonstrate four significant ways in which ‘found’ data can complement the more conventional ‘made’ data: firstly, in moving beyond constraints in scope (in terms of coverage, size, and temporality); secondly, in providing objective, quantitative measures where conventional research has had to rely on self-reported data; thirdly, in reaching populations that have proven difficult to access with conventional research methods; and lastly in its potential for evaluating real-world interventions. We discuss each of these opportunities in turn.

Firstly, many of the examples of ‘found’ data described here are remarkable in their broad scope and coverage. The constraints of conventional ‘made’ data have provided much of the impetus for exploring the potential of repurposed data. Advocates of ‘found’ data suggest that automation could reduce the burden of data collection [ 8 , 21 ]. It follows that a reduction in burden would allow more data to be collected over a longer period, both because of reduced costs and also due to reduced participant burden. This was particularly evident in the retail sales literature. RCTs or evaluations could automatically be updated with long-term data without having to collect a lot of information from participants.

Secondly, automated data collection could make an important contribution where conventional methods rely on self-reported information. There is much research that has documented the systematic biases, which have plagued obesity-related research through individuals misreporting their weight, dietary intake, or physical activity [ 72 ]. Other important factors that have proven traditionally difficult to measure include environmental characteristics which are theorised to have a role in the aetiology of obesity [ 73 , 74 ]. Data from transport and geospatial sources, in particular, could offer a means of capturing environmental features, although work may still be needed to develop meaningful, validated metrics. Given the suspected multi-faceted influences on obesity [ 75 ], the ability to measure specific aspects of the aetiology of obesity will help to build a more complete picture of its determinants. Thus, the opportunities afforded through objective data automatically collected from ‘found’ data could revolutionise our understanding of many complex areas [ 56 ]. The ability to quantify increasingly complex scenarios could also prove invaluable for predictive explorations, such as investigating system dynamics or agent-based modelling [ 76 ].

Thirdly, we can leverage the broad scope of these big data to explore hard-to-reach populations that conventional data are unable to access or provide precise estimates on [ 56 , 77 ]. For example, the Health Survey for England 2014 [ 78 ], one of the largest and most comprehensive sources of data on health-related behaviours ( n  = 10, 041), included only 1332 non-White individuals. Understanding the role of ethnicity, a key non-modifiable factor in obesity research, becomes problematic here. Big data can help, and can be extended to smaller groups as well. Linked to this, the growing interest in understanding the heterogeneity of obesity [ 79 ] can be improved through capturing more nuanced data to examine the interactions between risk factors and behavioural characteristics.

Finally, ‘found’ data provide a key opportunity for quasi-experimental research, by which we mean natural experiments that assess the impact of a policy or intervention. Examples from our review included evaluations of commercial weight management programmes [ 28 , 29 , 30 , 31 , 35 ], and assessing the impacts of events as diverse as infrastructure changes (e.g. new cycle routes) [ 67 ], popular gaming apps [ 68 , 69 ], changes to taxation on obesity-related commodities (e.g. sugar-sweetened beverages) [ 10 , 14 ] or local campaigns [ 13 , 20 ]. These examples illustrate the value of repurposed data for assessing real-world change. For example, without ‘found’ data, conventional methods would have required a cohort recruited well before an intervention or policy was implemented, with longitudinal collection of data. Using repurposed data that have been collected consistently for an adequate period of time, on the other hand, means that timely, longitudinal patterns can be explored, without a costly and lengthy lead-in. Although necessarily observational, and whilst there may be difficulties in finding appropriate comparators, the implications for the evaluation of public health (and other) policies are obvious. A number of these quasi-experimental studies adopted a combined approach [ 14 , 67 ], complementing the use of ‘found’ data with a more conventional research design, which illustrates perhaps one of the ways the limitations of big data could be addressed.

Quasi-experimental studies were rare for some types of data—namely travel, geospatial and social media data—and published studies in these categories predominantly focussed on descriptive, rather than causal, questions. This could be a promising area for future research: if causal investigation could broaden across multiple levels of determinants, such as those described by the Social-Ecological Model [ 80 ], from the individual to the structural, the ability to look at multiple factors across multiple scales might better allow us to begin to unpack the complexity of obesity development and prevention. Mapping the possible data sources that would allow this is an important first step to realising multi-level research, and forms the basis of the subsequent paper from our network (reference pending).

These opportunities are not without challenges. Many of the limitations described in this review are not necessarily new. For example, ‘found’ data sets typically comprise convenience samples [ 56 ]. However, the use of ‘found’ data also throws up some distinct challenges, such as:

ethical and legal questions around access and ownership of data

commercial sensitivities and potential costs

lack of control over data acquisition

questions over attributional adequacy—big data are often mono-thematic with great depth but limited breadth—and the clinical relevance of measurements

finding appropriate comparators

new skills and capabilities necessary for data processing, management and linkage.

These challenges have been well described by colleagues in relation to other health outcomes [ 2 , 7 , 56 ], and a further detailed exposition of these limitations is not possible here. However, addressing these issues will be of vital importance to enable utilisation of these data as well as considering the profound implications in terms of validity.

Accessibility to each data type was a common barrier to the usage of big data in obesity-related research. Many data types were held by industrial partners who are not always willing to permit researchers to use this information (although there are numerous examples where commercial data are being utilised for research purposes) or the costs associated with usage were prohibitive. Recently, multiple trusted third parties have been established to provide indirect access to such data and help bridge such gaps between industry and researchers (e.g. Consumer Data Research Centre in UK). Social media and geospatial data were more often openly available, hence the preponderance of studies utilising this type of information. Time and cost were minimal issues in reducing access, and when compared to traditional data, found data can be more efficient in terms of time and cost for data collection [ 3 ]. While there is no natural order to the quality or reliability of found data, we advocate that the pitfalls of ‘big data research’ are no different from traditional research. Any data should be assessed for its representativeness or bias no matter how big or small. For example, while Twitter data were the most common data source encountered in the review, the key limitation of this information is that it is not generalisable to whole population [ 56 ].

It is perhaps as important to comment on the gaps in data usage. The literature described here demonstrate initial forays into big data usage in the field of obesity. However, there are examples of ‘found’ data usage in other research areas that were notably absent in the obesity literature. For example, we did not observe any studies, which made use of ‘found’ data in the form of physiological or biological measurements, although measurement is becoming possible through smartphone technologies (e.g. peripheral capillary oxygen saturation or heart rate) [ 81 ]. This highlights that there are many future opportunities in exploring untapped data sources.

Limitations of the review

This review was not intended as an exhaustive examination of obesity research using ‘found’ data; rather, the aim was to illustrate the opportunities afforded by such data. This was important to demonstrate how and why such forms of data have been used in obesity research to date, and provide some key opportunities as to what can be achieved with such data in the future. It is also important to note that the scope of this synthesis was limited to academic literature.

The focus here was on ‘found’ data, repurposed for research, rather than on ‘big data’. Big data are not synonymous with ‘found’ data. However, much of the data described as ‘big’ has been repurposed from non-research-specific sources. This, we believe, is where much of the opportunity of big data lies: where data are collected anyway, its scope in terms of coverage, timeliness and automation could make a real, fresh contribution to the ways we are able to measure behavioural and environmental variables. By focussing on ‘found’ data, we hoped to identify its potential as well as the concomitant challenges, regardless of size, ‘big’ or ‘small’. Some of the studies described would not be considered ‘big’ by most, yet these smaller examples help to reveal or address potential problems with validity or data processing. In many cases, it is apparent that these need to be resolved at this smaller scale before upscaling to larger data sets.

Our focus has meant that some undeniably ‘big’ data sets are absent from our narrative: health registers and genetic databases were beyond our scope, yet their potential in obesity research is apparent. Many of the advantages described for ‘found’ data also apply to these data types: for example, health registers offer great scope in terms of volume and longitudinal and geographical coverage. However, ‘found’ data are an as yet under-utilised source of information, and many of the opportunities have yet to be exploited. ‘Found’ data also come with unique challenges to processing, storage and interpretation, given that they are created outside a research environment, and are therefore worthy of separate attention.

Conclusions

This paper has shown the limited extent to which ‘found’ data have been employed in academic obesity research to date, as well as describing the unique contribution such data can add to conventional research. The examples from the literature demonstrate how the merit of such data lies not in their novelty, but in the benefits they add over and above, or in combination with, conventionally collected data. However, alongside these new opportunities, there are new and distinct challenges. There is still a need to investigate ways to combine these new forms of data with conventional research to increase confidence in their validity and interpretation.

Despite widespread recognition of the opportunities across a broad spectrum of disciplines and data types, the potential of ‘found’ data has not yet been fully realised, and the impact on academic obesity research has been limited. In part, this may be due to limited data access, or even a lack of awareness about the data that may be available. The aim of the next paper from the ESRC Strategic Network for Obesity (reference pending) is to highlight the potential sources of data for further research of this type, many of which are as yet untapped.

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Acknowledgements

The ESRC Strategic Network for Obesity was funded via Economic and Social Research Council grant number ES/N00941X/1. We would like to thank all of the network investigators ( www.cdrc.ac.uk/research/obesity/investigators/ ) and members ( www.cdrc.ac.uk/research/obesity/network-members/ ) for their participation in network meetings and discussion, which contributed to the development of this paper. Additional thanks are owed to Daniel Lewis for his insightful comments on the manuscript.

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Timmins, K.A., Green, M.A., Radley, D. et al. How has big data contributed to obesity research? A review of the literature. Int J Obes 42 , 1951–1962 (2018). https://doi.org/10.1038/s41366-018-0153-7

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DOI : https://doi.org/10.1038/s41366-018-0153-7

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• Continuing Education Activity

Obesity is the excessive or abnormal accumulation of fat or adipose tissue in the body that may impair health. Obesity has become an epidemic which has worsened for the last 50 years. In the United States, the economic burden is estimated to be about $100 billion annually. Obesity is a complex disease and has multifactorial etiology. It is the second most common cause of preventable death after smoking. This activity reviews the causes, pathophysiology, presentation, and complications of obesity and highlights the role of the interprofessional team in its management.

• Recall the epidemiology of obesity.
• Describe the pathophysiology of obesity.
• Summarize the treatment options for obesity.
• Explore modalities to improve care coordination among interprofessional team members in order to improve outcomes for patients affected by obesity.
• Introduction

Obesity is the excessive or abnormal accumulation of fat or adipose tissue in the body that impairs health via its association with the risk of development of diabetes mellitus, cardiovascular disease, hypertension, and hyperlipidemia. It is a significant public health epidemic which has progressively worsened over the past 50 years. Obesity is a complex disease and has a multifactorial etiology. It is the second most common cause of preventable death after smoking. Obesity needs multiprong treatment strategies and may require lifelong treatment. A 5% to 10% weight loss can significantly improve health, quality of life, and economic burden of an individual and a country as a whole. [1] [2] [3] [4] [5]

Obesity has enormous healthcare costs exceeding $700 billion each year. The economic burden is estimated to be about $100 billion annually in the United States alone. The body mass index (BMI) is used to define obesity, which is calculated as weight (kg)/height(m). While the BMI does correlate with body fat in a curvilinear fashion, it may not be as accurate in Asians and older people,  where a normal BMI may conceal underlying excess fat. Obesity can also be estimated by assessing skin thickness in the triceps, biceps, subscapular, and supra-iliac areas. Dural energy radiographic absorptiometry (DEXA)  scan may also be used to assess fat mass.

Obesity is the result of an imbalance between daily energy intake and energy expenditure, resulting in excessive weight gain. Obesity is a multifactorial disease caused by a myriad of genetic, cultural, and societal factors.  Various genetic studies have shown that obesity is extremely heritable, with numerous genes identified with adiposity and weight gain. Other causes of obesity include reduced physical activity, insomnia, endocrine disorders, medications, the accessibility and consumption of excess carbohydrates and high-sugar foods, and decreased energy metabolism. 

The most common syndromes associated with obesity include Prader-Willi syndrome and MC4R  syndromes, less commonly fragile X, Bardet-Beidl syndrome, Wilson Turner congenital leptin deficiency, and Alstrom syndrome.

• Epidemiology

Nearly one-third of adults and about 17% of adolescents in the United States are obese. According to the Centers for Disease Control and Prevention (CDC)'s 2011-2012 data, one out of five adolescents, one out of six elementary school-age children, and one out of 12 preschool-age children are obese. Obesity is more prevalent in African Americans, followed by Hispanics and Whites. Southern US states have the highest prevalence, followed by the Midwest, Northeast, and the West.

Obesity rates are increasing at a staggering rate worldwide, affecting over 500 million adults.  

• Pathophysiology

Obesity is associated with cardiovascular disease, dyslipidemia, and insulin resistance, causing diabetes, stroke, gallstones, fatty liver, obesity, hypoventilation syndrome, sleep apnea, and cancers.

The association between genetics and obesity is already well-established by multiple studies. The  FTO gene is associated with adiposity. This gene might harbor multiple variants that increase the risk of obesity.

Leptin is an adipocyte hormone that reduces food intake and body weight. Cellular leptin resistance is associated with obesity. Adipose tissue secretes adipokines and free fatty acids, causing systemic inflammation, which causes insulin resistance and increased triglyceride levels, subsequently contributing to obesity.

Obesity can cause increased fatty acid deposition in the myocardium, causing left ventricular dysfunction. It has also been shown to alter the renin-angiotensin system, causing increasing salt retention and elevated blood pressure.

Besides total body fat, the following also increase the morbidity of obesity:

• Waist circumference (abdominal fat carries a poor prognosis)
• Fat distribution (body fat heterogeneity)
• Intra-abdominal pressure
• Age of onset of obesity

The body fat distribution is important in assessing the risk for cardiometabolic health. The distribution of excess visceral fat is likely to increase the risk of cardiovascular disease. [6] [7] [8]  Ruderman et al [9]  introduced the concept of metabolic obese normal weight(MONW) subjects with normal BMI suffer from metabolic complications normally found in obese individuals.

Metabolically healthy obese (MHO) Individuals have a BMI over 30 kg/m 2 but do not have the characteristics of insulin resistance or dyslipidemia [10] [11]  

Adipocytes have been shown to have an inflammatory and prothrombotic activity, which can increase the risk of strokes. Adipokines are cytokines mainly produced by adipocytes and preadipocytes; in obesity, macrophages invading the tissue also produce adipokines.  [12] [13] . 

Altered adipokine secretion causes chronic low-grade inflammation, which may cause altered glucose and lipid metabolism and contribute to cardiometabolic risk in visceral obesity.  [12]

Adiponectin has insulin-sensitizing and anti-inflammatory properties, and the circulating levels are inversely proportional to visceral obesity.

• History and Physical

All children six years and older, adolescents, and all adults should be screened for obesity according to the United States Preventative Services Task Force (USPSTF) recommendations.

Physicians should carefully screen for underlying causes contributing to obesity. A complete history should include:

• Childhood weight history
• Prior weight loss efforts and results
• Complete nutrition history
• Sleep patterns
• Physical activity
• Associated past medical histories like cardiovascular, diabetes, thyroid, and depression
• Surgical history
• Medications that can promote weight gain
• Social histories of tobacco and alcohol use
• Family history

A complete physical examination Should be done and should include body mass index (BMI) measurement, weight circumference, body habitus, and vitals.

Obesity focus findings like acne, hirsutism, skin tags, acanthosis nigricans, striae, Mallampati scoring, buffalo hump, fat pad distribution, irregular rhythms, gynecomastia, abdominal pannus, hepatosplenomegaly, hernias, hypoventilation, pedal edema, varicoceles, stasis dermatitis, and gait abnormalities can be present.

A standard screening tool for obesity is the measurement of body mass index (BMI). BMI is calculated using weight in kilograms divided by the square of height in meters. [14] [15] [16] [17] [18]  Obesity can be classified according to BMI:

• Underweight: less than 18.5 kg/m 2
• Normal range: 18.5 kg/m2 to 24.9 kg/m 2
• Overweight: 25 kg/m2 to 29.9 kg/m 2
• Obese, Class I: 30 kg/m2 to 34.9 kg/m 2
• Obese, Class II: 35 kg/m2 to 39.9 kg/m 2
• Obese, Class III: more than 40 kg/m 2

The waist-to-hip ratio should be measured; in men, more than 1:1, and in women, more than 0:8 is considered significant.

Further evaluation studies like skinfold thickness, bioelectric impedance analysis, CT, MRI, DEXA, water displacement, and air densitometry studies can be done.

Laboratory studies include a complete blood picture, basic metabolic panel, renal function, liver function study, lipid profile, HbA1C, TSH, vitamin D levels, urinalysis, CRP, and other studies like ECG and sleep studies can be done for evaluating associated medical conditions. 

• Treatment / Management

Obesity causes multiple comorbid and chronic medical conditions, and physicians should have a multiprong approach to the management of obesity. Practitioners should individualize treatment, treat underlying secondary causes of obesity, and focus on managing or controlling associated comorbid conditions. Management should include dietary modification, behavior interventions, medications, and surgical intervention if needed.

The dietary modification should be individualized with close monitoring of regular weight loss. Low-calorie diets are recommended. Low calorie could be carbohydrate or fat restricted. A low-carbohydrate diet can produce greater weight loss in the first months compared to a low-fat diet. The patient's adherence to their diet should frequently be emphasized.

Behavior Interventions: The  USPSTF recommends obese patients be referred for intensive behavior interventions. Several psychotherapeutic interventions are available, which include motivational interviewing, cognitive behavior therapy, dialectical behavior therapy, and interpersonal psychotherapy. Behavior interventions are more effective when they are combined with diet and exercise.

Medications: Antiobesity medications can be used for BMI greater than or equal to 30 or BMI greater than or equal to 27 with comorbidities. Medications can be combined with diet, exercise, and behavior interventions. FDA-approved antiobesity medications include phentermine, orlistat, liraglutide, semaglutide, diethylpropion, phentermine/topiramate, naltrexone/bupropion, setmelanotide, and phendimetrazine. All the agents are used for long-term weight management. Orlistat is usually the first choice because of its lack of systemic effects due to limited absorption.

Surgery: Indications for surgery are a BMI greater or equal to 40 or a BMI of 35 or greater with severe comorbid conditions. The patient should be compliant with post-surgery lifestyle changes, office visits, and exercise programs. Patients should have an extensive preoperative evaluation of surgical risks. Commonly performed bariatric surgeries include adjustable gastric banding, Rou-en-Y gastric bypass, and sleeve gastrectomy. Rapid weight loss can be achieved with a gastric bypass, and it is the most commonly performed procedure. Early postoperative complications include leak, infection, postoperative bleeding, thrombosis, and cardiac events. Late complications include malabsorption, vitamin and mineral deficiency, refeeding syndrome, and dumping syndrome. [19] [20] [21]

Weight loss associated complications

When weight loss is rapid, it is also associated with complications that include:

• Electrolyte abnormalities (esp, hypokalemia)
• Cardiac arrhythmias
• Hyperuricemia
• Cholelithiasis
• Mood and behavior alterations

Complications associated with bariatric surgery

• Wound dehiscence
• Malabsorption
• Dumping syndrome
• Post-surgery diarrhea
• Vitamin and nutrient deficiency
• Anastomotic leaks
• Failed surgery
• Differential Diagnosis
• Adipose dolorosa 
• Cushing syndrome
• Hypothyroidism
• Iatrogenic Cushing syndrome
• Kallman syndrome and idiopathic hypogonadotropic hypogonadism 
• Generalized lipodystrophy 
• Polycystic ovarian disease

Obesity has enormous morbidity and mortality rates. Obese patients have a high risk of adverse cardiac events and stroke. In addition, the quality of life is poor. Factors that worsen morbidity include:

• Amount of central adiposity
• Severity of obesity
• Associated comorbidity
• Pearls and Other Issues

Management of obesity should also include prevention strategies with physical activity, exercise, nutrition, and weight maintenance.

• Enhancing Healthcare Team Outcomes

The obesity epidemic continues to worsen and has become a public health issue. The management and prevention of obesity is best done with an interprofessional team that includes a bariatric nurse, surgeon, internist, primary care provider, endocrinologist, and a pharmacist. There is no cure for obesity, and almost every treatment available has limitations and potential adverse effects.

The key is to educate the patient on the importance of changes in lifestyle. All clinicians who look after obese patients have the onus to educate patients on the harms of the disorders. No intervention works if the patient remains sedentary. Even after surgery, some type of exercise program is necessary to prevent weight gain. So far, there is no magic bullet to reverse obesity- all treatments have high failure rates, and some, like surgery, also have life-threatening complications. There is an important need for collaboration between the fast-food industry, schools, physical therapists, dietitians,  clinicians, and public health authorities to create better and safer eating habits.

Lifestyle changes alone can help obese people reverse the weight gain, but the problem is most people are not motivated to exercise. [21] [22]

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BMI chart with obesity classifications adopted from the WHO 1998 report. Contributed by the World Health Organization - "Report of a WHO consultation on obesity. Obesity Preventing and Managing a Global Epidemic."

Disclosure: Kiran Panuganti declares no relevant financial relationships with ineligible companies.

Disclosure: Minhthao Nguyen declares no relevant financial relationships with ineligible companies.

Disclosure: Ravi Kshirsagar declares no relevant financial relationships with ineligible companies.

This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits others to distribute the work, provided that the article is not altered or used commercially. You are not required to obtain permission to distribute this article, provided that you credit the author and journal.

• Cite this Page Panuganti KK, Nguyen M, Kshirsagar RK. Obesity. [Updated 2023 Aug 8]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

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